From my SciPy 2017 talk, the combination of pint.Quantity for unit support with masked arrays produces problems not seen with either individually:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import pint
units = pint.UnitRegistry()
data = np.random.randn(30,)
data_units = data * units.meters
data_masked = np.ma.array(data, mask=data<0.)
data_masked_units = data_masked * units.meters
fig, axes = plt.subplots(1, 3, sharex=True, sharey=True, figsize=(8, 4))
axes[0].plot(data_units)
axes[1].plot(data_masked)
axes[2].plot(data_masked_units)
produces:
From my SciPy 2017 talk, the combination of pint.Quantity for unit support with masked arrays produces problems not seen with either individually:
produces: