Major refactoring of RFCP backend: - Modular propagation models (8 models) - SharedMemoryManager for terrain data - ProcessPoolExecutor parallel processing - WebSocket progress streaming - Building filtering pipeline (351k → 15k) - 82 unit tests Performance: Standard preset 38s → 5s (7.6x speedup) Known issue: Detailed preset timeout (fix in 3.1.0)
76 lines
2.0 KiB
Python
76 lines
2.0 KiB
Python
"""
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Longley-Rice Irregular Terrain Model (ITM).
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Best for:
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- VHF/UHF over irregular terrain
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- Point-to-point links
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- Distances 1-2000 km
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Note: This is a simplified area-mode version.
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Full implementation requires terrain profile data.
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Reference: NTIA Report 82-100
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"""
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import math
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from app.propagation.base import PropagationModel, PropagationInput, PropagationOutput
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class LongleyRiceModel(PropagationModel):
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@property
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def name(self) -> str:
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return "Longley-Rice"
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@property
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def frequency_range(self) -> tuple:
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return (20, 20000) # 20 MHz to 20 GHz
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@property
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def distance_range(self) -> tuple:
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return (1000, 2000000) # 1-2000 km
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def calculate(self, input: PropagationInput) -> PropagationOutput:
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"""
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Simplified Longley-Rice (area mode).
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For proper implementation, use splat! or NTIA ITM reference.
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"""
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f = input.frequency_mhz
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d = max(input.distance_m / 1000, 1.0)
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h1 = max(input.tx_height_m, 1.0)
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h2 = max(input.rx_height_m, 1.0)
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# Terrain irregularity parameter (simplified)
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delta_h = input.terrain_roughness_m or 90 # Default: rolling hills
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# Free space loss
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L_fs = 32.45 + 20 * math.log10(d) + 20 * math.log10(f)
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# Terrain clutter loss (simplified)
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if delta_h < 10:
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L_terrain = 0 # Flat
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elif delta_h < 50:
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L_terrain = 5 # Gently rolling
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elif delta_h < 150:
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L_terrain = 10 # Rolling hills
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else:
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L_terrain = 15 # Mountains
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# Height gain
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h_eff = h1 + h2
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height_gain = 10 * math.log10(h_eff / 20) if h_eff > 20 else 0
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L = L_fs + L_terrain - height_gain
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return PropagationOutput(
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path_loss_db=L,
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model_name=self.name,
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is_los=delta_h < 10 and d < 10,
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breakdown={
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"free_space_loss": L_fs,
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"terrain_loss": L_terrain,
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"height_gain": height_gain,
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},
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)
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