Source code for pySimBlocks.blocks.interfaces.external_output

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import numpy as np
from pySimBlocks.core.block import Block


[docs] class ExternalOutput(Block): """External output interface block. Pass-through block for exposing model signals to the real-time external side. Accepts scalar, (n,) or (n,1) inputs and forwards them as a strict (n,1) column vector. The output shape is frozen after the first non-None input and cannot change during the simulation. """ direct_feedthrough = True def __init__(self, name: str, sample_time: float | None = None): """Initialize an ExternalOutput block. Args: name: Unique identifier for this block instance. sample_time: Sampling period in seconds, or None to use the global simulation dt. """ super().__init__(name, sample_time) self.inputs["in"] = None self.outputs["out"] = None self._resolved_shape: tuple[int, int] | None = None # -------------------------------------------------------------------------- # Public methods # --------------------------------------------------------------------------
[docs] def initialize(self, t0: float) -> None: """Set the output to None if no input is available, or forward the input. Args: t0: Initial simulation time in seconds. """ u = self.inputs["in"] if u is None: self.outputs["out"] = None return self.outputs["out"] = self._to_col_vec(u)
[docs] def output_update(self, t: float, dt: float) -> None: """Forward the input to the output as a column vector. Args: t: Current simulation time in seconds. dt: Current time step in seconds. Raises: RuntimeError: If input ``in`` is not set. ValueError: If the input shape is incompatible or has changed. """ u = self.inputs["in"] if u is None: raise RuntimeError(f"[{self.name}] Missing input 'in'.") self.outputs["out"] = self._to_col_vec(u)
[docs] def state_update(self, t: float, dt: float) -> None: """No-op: ExternalOutput carries no internal state."""
# -------------------------------------------------------------------------- # Private methods # -------------------------------------------------------------------------- def _to_col_vec(self, value) -> np.ndarray: """Normalize value to a (n,1) column vector and enforce frozen shape.""" arr = np.asarray(value, dtype=float) if arr.ndim == 0: arr = arr.reshape(1, 1) elif arr.ndim == 1: arr = arr.reshape(-1, 1) elif arr.ndim == 2 and arr.shape[1] == 1: pass else: raise ValueError( f"[{self.name}] Input 'in' must be scalar, (n,), or (n,1). Got shape {arr.shape}." ) if self._resolved_shape is None: self._resolved_shape = arr.shape elif arr.shape != self._resolved_shape: raise ValueError( f"[{self.name}] Input 'in' shape changed: expected {self._resolved_shape}, got {arr.shape}." ) return arr