L2SS-436: Conjugate XSTs if they are from the other triangle of the matrix...

L2SS-436: Conjugate XSTs if they are from the other triangle of the matrix (a<b for a baseline (a,b))

devices/devices/sdp/statistics_collector.py

@@ -131,6 +131,8 @@ class XSTCollector(StatisticsCollector):
 
             # Last value array we've constructed out of the packets
             "xst_blocks":            numpy.zeros((self.MAX_BLOCKS, self.BLOCK_LENGTH * self.BLOCK_LENGTH * self.VALUES_PER_COMPLEX), dtype=numpy.int64),
+            # Whether the values are actually conjugated
+            "xst_conjugated":        numpy.zeros((self.MAX_BLOCKS,), dtype=numpy.bool_),
             "xst_timestamps":        numpy.zeros((self.MAX_BLOCKS,), dtype=numpy.float64),
             "xst_subbands":          numpy.zeros((self.MAX_BLOCKS,), dtype=numpy.uint16),
             "integration_intervals": numpy.zeros((self.MAX_BLOCKS,), dtype=numpy.float32),
@@ -162,6 +164,14 @@ class XSTCollector(StatisticsCollector):
             if fields.first_baseline[antenna] % self.BLOCK_LENGTH != 0:
                 raise ValueError("Packet describes baselines starting at %s, but we require a multiple of BLOCK_LENGTH=%d" % (fields.first_baseline, self.MAX_INPUTS))
 
+        # Make sure we always have a baseline (a,b) with a>=b. If not, we swap the indices and mark that the data must be conjugated when processed.
+        first_baseline = fields.first_baseline[antenna]
+        if first_baseline[0] < first_baseline[1]:
+            conjugated = True
+            first_baseline = (first_baseline[1], first_baseline[0])
+        else:
+            conjugated = False
+
         # the payload contains complex values for the block of baselines of size BLOCK_LENGTH x BLOCK_LENGTH
         # starting at baseline first_baseline.
         #
@@ -176,6 +186,7 @@ class XSTCollector(StatisticsCollector):
 
         self.parameters["xst_blocks"][block_index][:fields.nof_statistics_per_packet] = fields.payload
         self.parameters["xst_timestamps"][block_index]        = numpy.float64(fields.timestamp().timestamp())
+        self.parameters["xst_conjugated"][block_index]        = conjugated
         self.parameters["xst_subbands"][block_index]          = numpy.uint16(fields.subband_index)
         self.parameters["integration_intervals"][block_index] = fields.integration_interval()
 
@@ -184,11 +195,16 @@ class XSTCollector(StatisticsCollector):
 
         matrix = numpy.zeros((self.MAX_INPUTS, self.MAX_INPUTS), dtype=numpy.complex64)
         xst_blocks = self.parameters["xst_blocks"]
+        xst_conjugated = self.parameters["xst_conjugated"]
 
         for block_index in range(self.MAX_BLOCKS):
             # convert real/imag int to complex float values. this works as real/imag come in pairs
             block = xst_blocks[block_index].astype(numpy.float32).view(numpy.complex64)
 
+            if xst_conjugated[block_index]:
+                # block is conjugated. conjugate back.
+                block = block.conjugate()
+
             # reshape into [a][b]
             block = block.reshape(self.BLOCK_LENGTH, self.BLOCK_LENGTH)
 

devices/devices/sdp/xst.py

@@ -118,6 +118,8 @@ class XST(Statistics):
     nof_payload_errors_R    = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "nof_payload_errors"}, dims=(XSTCollector.MAX_FPGAS,), datatype=numpy.uint64)
     # latest XSTs
     xst_blocks_R            = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_blocks"}, dims=(XSTCollector.BLOCK_LENGTH * XSTCollector.BLOCK_LENGTH * XSTCollector.VALUES_PER_COMPLEX, XSTCollector.MAX_BLOCKS), datatype=numpy.int64)
+    # whether the values in the block are conjugated
+    xst_conjugated_R        = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_conjugated"}, dims=(XSTCollector.MAX_BLOCKS,), datatype=numpy.bool_)
     # reported timestamp for each row in the latest XSTs
     xst_timestamp_R         = attribute_wrapper(comms_id=StatisticsClient, comms_annotation={"type": "statistics", "parameter": "xst_timestamps"}, dims=(XSTCollector.MAX_BLOCKS,), datatype=numpy.uint64)
     # which subband the XSTs describe