f3f1fc2c49
Pass tx params copy to ComputeSnr, to prevent pathloss to be incorrectly accumulated over time
87 lines
2.3 KiB
Python
87 lines
2.3 KiB
Python
#!/bin/python3
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# Copyright (c) 2020, University of Padova, Dep. of Information Engineering, SIGNET lab
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# Copyright (c) 2025, Centre Tecnologic de Telecomunicacions de Catalunya (CTTC)
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#
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# SPDX-License-Identifier: GPL-2.0-only
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import matplotlib.animation as animation
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import matplotlib.patches as patches
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import matplotlib.pyplot as plt
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#
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# Plot the traces generated by three-gpp-v2v-channel-example
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#
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import pandas as pd
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# Load the data
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df = pd.read_csv("example-output.txt", sep=r"\s+", comment="#")
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df = df.iloc[::10, :]
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# Column indices (adjust if needed)
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TIME = 0
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TX_X = 1
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TX_Y = 2
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RX_X = 3
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RX_Y = 4
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SNR = 6
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# Create the figure and subplots
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fig, (ax_map, ax_snr) = plt.subplots(1, 2, figsize=(12, 6))
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# Map plot config
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ax_map.set_xlim(-25, 600)
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ax_map.set_ylim(-25, 1000)
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ax_map.set_xlabel("X [m]")
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ax_map.set_ylabel("Y [m]")
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ax_map.set_aspect("equal")
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tx_circle = patches.Circle((0, 0), 5, color="blue", alpha=0.35)
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rx_circle = patches.Circle((0, 0), 5, color="red", alpha=0.35)
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ax_map.add_patch(tx_circle)
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ax_map.add_patch(rx_circle)
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# SNR plot config
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ax_snr.set_xlim(0, 40)
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ax_snr.set_ylim(-20, 100)
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ax_snr.set_xlabel("Time [s]")
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ax_snr.set_ylabel("SNR [dB]")
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ax_snr.grid(True)
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(snr_line,) = ax_snr.plot([], [], "k-")
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buildings = pd.read_csv("buildings.txt", sep=r"\s+", comment="#", header=None)
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building_patches = []
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for idx, row in buildings.iterrows():
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x0, y0, x1, y1 = row
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width = x1 - x0
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height = y1 - y0
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rect = patches.Rectangle((x0, y0), width, height, color="gray", alpha=0.5)
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ax_map.add_patch(rect)
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building_patches.append(rect)
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# Animation update function
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def update(frame):
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row = df.iloc[frame]
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tx_circle.set_center((row.iloc[TX_X], row.iloc[TX_Y]))
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rx_circle.set_center((row.iloc[RX_X], row.iloc[RX_Y]))
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snr_line.set_data(df.iloc[: frame + 1, TIME], df.iloc[: frame + 1, SNR])
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ax_map.set_title(f"Time = {row.iloc[TIME]:.1f} s")
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return tx_circle, rx_circle, snr_line
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# Run animation
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ani = animation.FuncAnimation(fig, update, frames=len(df), interval=0.001, blit=False)
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# Save animation
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ani.save("map.gif", writer="pillow")
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# Save final SNR plot separately
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plt.figure()
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plt.plot(df.iloc[:, TIME], df.iloc[:, SNR], "k-")
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plt.xlabel("Time [s]")
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plt.ylabel("SNR [dB]")
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plt.grid(True)
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plt.xlim(0, 40)
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plt.ylim(-20, 100)
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plt.savefig("snr.png")
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