import xarray as xr
import pandas as pd
import numpy as np


# Generate two arrays of random numbers
rand1 = np.random.randn(15)
rand2 = np.random.randn(12)

# Create a 5x3 DataArray from rand1 with labeled dimensions and convert it to a Dataset
data1 = xr.DataArray(
    rand1.reshape((5, 3)),
    dims=("x", "y"),
    coords={"x": [1, 2, 3, 4, 5], "y": [1, 2, 3]},
).to_dataset(name="value")

# Create a 3x4 DataArray from rand2 with labeled dimensions and convert it to a Dataset
base1 = xr.DataArray(
    rand2.reshape(3, 4),
    dims=("x", "y"),
    coords={"x": [100, 200, 300], "y": [1, 2, 3, 4]},
).to_dataset(name="base_value")

# Create an equivalent Dataset to data1 using a pandas MultiIndex DataFrame
data2 = xr.Dataset.from_dataframe(
    pd.DataFrame(
        rand1,
        columns=["value"],
        index=pd.MultiIndex.from_product([[1, 2, 3, 4, 5], [1, 2, 3]], names=["x", "y"]),
    )
)

# Create an equivalent Dataset to base1 using a pandas MultiIndex DataFrame
base2 = xr.Dataset.from_dataframe(
    pd.DataFrame(
        rand2,
        columns=["base_value"],
        index=pd.MultiIndex.from_product([[100, 200, 300], [1, 2, 3, 4]], names=["x", "y"]),
    )
)

# Verify that the two ways of constructing the datasets yield the same results
# These succeed
assert data1.equals(data2)
assert base1.equals(base2)

# Reindex `data1` to align its 'y' dimension with the 'y' coordinates of `base1`
data1b = data1.reindex(y=base1.y)  # succeeds

# Reindex `data1` again, but now aligning with `base2` (same structure as `base1`)
# fails with
# RuntimeError: Cannot set name on a level of a MultiIndex. Use 'MultiIndex.set_names' instead.
data2b = data1.reindex(y=base2.y)