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Add antenna RSSI data from the field
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load("@pip_deps//:requirements.bzl", "requirement") | ||
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package(default_visibility = ["//visibility:public"]) | ||
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py_binary( | ||
name = "antenna_rssi_main", | ||
srcs = ["antenna_rssi_main.py"], | ||
data = ["//analysis/scum/antenna/data:antenna_rssi_data"], | ||
deps = [ | ||
requirement("absl-py"), | ||
requirement("matplotlib"), | ||
requirement("pandas"), | ||
requirement("SciencePlots"), | ||
], | ||
) |
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import matplotlib.pyplot as plt | ||
import pandas as pd | ||
import scienceplots | ||
from absl import app, flags, logging | ||
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FLAGS = flags.FLAGS | ||
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def plot_antenna_rssi(data: str) -> None: | ||
"""Plots the antenna RSSI. | ||
Each column in the data corresponds to an antenna. | ||
Args: | ||
data: Data filename. | ||
""" | ||
# Open the antenna RSSI data file. | ||
df = pd.read_csv(data, comment="#") | ||
logging.info(df.describe()) | ||
distance_column = df.columns[0] | ||
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# Group by antenna. | ||
df_by_antenna = df.groupby(distance_column) | ||
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# Plot the mean and standard deviation of the RSSI. | ||
plt.style.use(["science", "grid"]) | ||
fig, ax = plt.subplots(figsize=(12, 8)) | ||
df_by_antenna.mean().plot(ax=ax, yerr=df_by_antenna.std(), marker="^") | ||
ax.set_ylabel("RSSI [dBm]") | ||
plt.show() | ||
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def main(argv): | ||
assert len(argv) == 1 | ||
plot_antenna_rssi(FLAGS.data) | ||
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if __name__ == "__main__": | ||
flags.DEFINE_string( | ||
"data", "analysis/scum/antenna/data/antenna_rssi_data_field.csv", | ||
"Data filename.") | ||
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app.run(main) |
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package(default_visibility = ["//visibility:public"]) | ||
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filegroup( | ||
name = "antenna_rssi_data", | ||
srcs = glob(["antenna_rssi_data_*.csv"]), | ||
) |
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# 20240716 | ||
# M2 | ||
# SCuM TX, OpenMote RX | ||
# Measured at the Delta field site on Bouldin Island | ||
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Distance [m],Rubber ducky [dBm],Solid ground PCB [dBm],Solid ground PCB rotated by 90° [dBm],Solid ground PCB over corn [dBm] | ||
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