Merge pull request #112 from SAR-ARD/bugfix/slice_id

support for scenes acquired in NRT Slicing mode

S1_NRB/ancillary.py

@@ -49,22 +49,37 @@ def check_acquisition_completeness(scenes, archive):
         groupsize = 3
         has_successor = True
         has_predecessor = True
-        if slice == 0:
-            raise RuntimeError(f'invalid value for sliceNumber: 0')
-        if n_slices == 0:
-            raise RuntimeError(f'invalid value for totalSlices: 0')
-        if slice == 1:  # first slice in the data take
-            groupsize -= 1
-            has_predecessor = False
-        if slice == n_slices:  # last slice in the data take
-            groupsize -= 1
-            has_successor = False
+
         f = '%Y%m%dT%H%M%S'
         td = timedelta(seconds=2)
         start = datetime.strptime(scene.start, f) - td
         start = datetime.strftime(start, f)
         stop = datetime.strptime(scene.stop, f) + td
         stop = datetime.strftime(stop, f)
+        ref = None
+        if slice == 0 or n_slices == 0:
+            # NRT slicing mode
+            ref = asf_select(sensor=scene.sensor,
+                             product=scene.product,
+                             acquisition_mode=scene.acquisition_mode,
+                             mindate=start,
+                             maxdate=stop)
+            match = [re.search(scene.pattern, x + '.SAFE').groupdict() for x in ref]
+            ref_start_min = min([x['start'] for x in match])
+            ref_stop_max = max([x['stop'] for x in match])
+            if ref_start_min == scene.start:
+                groupsize -= 1
+                has_predecessor = False
+            if ref_stop_max == scene.stop:
+                groupsize -= 1
+                has_successor = False
+        else:
+            if slice == 1:  # first slice in the data take
+                groupsize -= 1
+                has_predecessor = False
+            if slice == n_slices:  # last slice in the data take
+                groupsize -= 1
+                has_successor = False
         # Do another database selection to get the scene in question as well as its potential
         # predecessor and successor by adding an acquisition time buffer of two seconds.
         group = archive.select(sensor=scene.sensor,
@@ -75,13 +90,15 @@ def check_acquisition_completeness(scenes, archive):
                                date_strict=False)
         group = identify_many(group)
         # if the number of selected scenes is lower than the expected group size,
-        # check whether the predecessor, the successor or both are missing.
+        # check whether the predecessor, the successor or both are missing by
+        # cross-checking with the ASF database.
         if len(group) < groupsize:
-            ref = asf_select(sensor=scene.sensor,
-                             product=scene.product,
-                             acquisition_mode=scene.acquisition_mode,
-                             mindate=start,
-                             maxdate=stop)
+            if ref is None:
+                ref = asf_select(sensor=scene.sensor,
+                                 product=scene.product,
+                                 acquisition_mode=scene.acquisition_mode,
+                                 mindate=start,
+                                 maxdate=stop)
             match = [re.search(scene.pattern, x + '.SAFE').groupdict() for x in ref]
             ref_start_min = min([x['start'] for x in match])
             ref_stop_max = max([x['stop'] for x in match])
@@ -321,6 +338,7 @@ def _log_process_config(logger, config):
     aoi_geometry        {config['aoi_geometry']}
     mindate             {config['mindate'].isoformat()}
     maxdate             {config['maxdate'].isoformat()}
+    date_strict         {config['date_strict']}
     sensor              {config['sensor']}
     acq_mode            {config['acq_mode']}
     product             {config['product']}

S1_NRB/snap.py

@@ -3,6 +3,8 @@
 import itertools
 import shutil
 from math import ceil
+from lxml import etree
+from dateutil.parser import parse as dateparse
 from spatialist import bbox, Raster
 from spatialist.envi import HDRobject
 from spatialist.ancillary import finder
@@ -161,7 +163,7 @@ def grd_buffer(src, dst, workflow, neighbors, buffer=100, gpt_args=None):
     Parameters
     ----------
     src: str
-        the file name of the source scene
+        the file name of the source scene in BEAM-DIMAP format.
     dst: str
         the file name of the target scene. Format is BEAM-DIMAP.
     workflow: str
@@ -182,6 +184,10 @@ def grd_buffer(src, dst, workflow, neighbors, buffer=100, gpt_args=None):
     scenes = identify_many([src] + neighbors, sortkey='start')
     wf = parse_recipe('blank')
     ############################################
+    # modify the slice number if it is 0
+    for scene in scenes:
+        nrt_slice_num(dim=scene.scene)
+    ############################################
     read_ids = []
     for scene in scenes:
         read = parse_node('Read')
@@ -925,3 +931,43 @@ def get_metadata(scene, outdir):
         raise RuntimeError(msg.format('\n'.join(wf_mli)))
     return {'azlks': azlks,
             'rlks': rlks}
+
+
+def nrt_slice_num(dim):
+    """
+    Compute a slice number for a scene acquired NRT Slicing mode.
+    In this mode both `sliceNumber` and `totalSlices` are 0 in the manifest.safe file.
+    `sliceNumber` is however needed in function :func:`~S1_NRB.snap.grd_buffer` for
+    the SNAP operator `SliceAssembly`.
+    The time from `segmentStartTime` to `last_line_time` is divided by
+    the acquisition duration (`last_line_time` - `first_line_time`).
+    `totalSlices` is set to 100, which is expected to exceed the maximum possible value.
+    
+    Parameters
+    ----------
+    dim: str
+        the scene in BEAM-DIMAP format
+
+    Returns
+    -------
+
+    """
+    with open(dim, 'rb') as f:
+        root = etree.fromstring(f.read())
+    abstract = root.xpath("//MDElem[@name='Abstracted_Metadata']")[0]
+    slice_num = abstract.xpath("./MDATTR[@name='slice_num']")[0]
+    if slice_num.text == '0':
+        flt = dateparse(abstract.xpath("./MDATTR[@name='first_line_time']")[0].text)
+        llt = dateparse(abstract.xpath("./MDATTR[@name='last_line_time']")[0].text)
+        sst = dateparse(root.xpath("//MDATTR[@name='segmentStartTime']")[0].text)
+        aqd = llt - flt
+        slice_num_new = str(int(round((llt - sst) / aqd)))
+        slice_num.text = slice_num_new
+        for item in root.xpath("//MDATTR[@name='sliceNumber']"):
+            item.text = slice_num_new
+        for item in root.xpath("//MDATTR[@name='totalSlices']"):
+            item.text = '100'
+        etree.indent(root, space='    ')
+        tree = etree.ElementTree(root)
+        tree.write(dim, pretty_print=True, xml_declaration=True,
+                   encoding='utf-8')

docs/api.rst

@@ -49,6 +49,7 @@ SNAP
         mli
         pre
         rtc
+        sgr
 
     .. rubric:: ancillary functions
 
@@ -58,6 +59,7 @@ SNAP
         find_datasets
         get_metadata
         postprocess
+        nrt_slice_num
 
 NRB
 ^^^