import numpy as np

readings = np.array([21.5, np.nan, 19.0, np.nan, 22.0])
valid_values = ~np.isnan(readings)
filtered_values = readings[valid_values]

samples = np.array(
    [
        [21.5, 0.98],
        [np.nan, 0.95],
        [19.0, np.nan],
        [22.0, 0.96],
    ]
)
complete_rows = ~np.isnan(samples).any(axis=1)
filtered_rows = samples[complete_rows]

print("valid value mask:", valid_values)
print("filtered values:", filtered_values)
print("remaining value NaNs:", np.isnan(filtered_values).any())
print("complete row mask:", complete_rows)
print("filtered rows:")
print(filtered_rows)
print("remaining row NaNs:", np.isnan(filtered_rows).any())