Merge pull request 'Expand Number of samples' (#22) from zfp-oss into main

Reviewed-on: #22

poetry.toml

@@ -0,0 +1,2 @@
+[virtualenvs.options]
+system-site-packages = true

src/ria_toolkit_oss/sdr/sdr.py

@@ -43,6 +43,13 @@ class SDR(ABC):
         self.tx_gain = None
         self._param_lock = threading.RLock()  # Reentrant lock
 
+        # Pending config consumed by rx() on first call and by _apply_sdr_config
+        # in the agent inference loop.  Subclasses that need different defaults
+        # (e.g. MockSDR) can overwrite these in their own __init__.
+        self.center_freq: float = 2.4e9
+        self.sample_rate: float = 10e6
+        self.gain: float = 40.0
+
     def record(self, num_samples: Optional[int] = None, rx_time: Optional[int | float] = None) -> Recording:
         """
         Create a radio recording of a given length. Either ``num_samples`` or ``rx_time`` must be provided.
@@ -100,6 +107,32 @@ class SDR(ABC):
         self._num_buffers_processed = 0
         return recording
 
+    def rx(self, num_samples: int) -> "np.ndarray":
+        """Return *num_samples* complex IQ samples as a 1-D complex64 array.
+
+        This is the interface used by the agent inference loop.  On first call,
+        ``init_rx()`` is invoked automatically using the values stored in
+        ``center_freq``, ``sample_rate``, and ``gain`` (set beforehand by
+        ``_apply_sdr_config``).  Subsequent calls stream directly.
+
+        Subclasses may override this for hardware-native capture APIs (e.g.
+        ``MockSDR`` uses AWGN generation; ``PlutoSDR`` could use
+        ``self.radio.rx()``).
+        """
+        if not self._rx_initialized:
+            gain = self.gain if isinstance(self.gain, (int, float)) else 40.0
+            self.init_rx(
+                sample_rate=self.sample_rate,
+                center_frequency=self.center_freq,
+                gain=gain,
+                channel=0,
+            )
+        recording = self.record(num_samples=num_samples)
+        # Recording.data is either a list of 1-D arrays (one per channel) or a
+        # 2-D ndarray (channels × samples).  Either way, index 0 is channel 0.
+        data = recording.data
+        return data[0] if hasattr(data, "__getitem__") else data
+
     def stream_to_zmq(self, zmq_address, n_samples: int, buffer_size: Optional[int] = 10000):
         """
         Stream iq samples as interleaved bytes via zmq.