Bug report: broadcasted weights with NaN lead to ValueError: assignment destination is read-only

[ahuang11]

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

obs2 = xr.DataArray(
    np.random.rand(3, 180, 360),
    coords=[
        pd.date_range("1/1/2000", "1/3/2000", freq="D"),
        np.linspace(-89.5, 89.5, 180),
        np.linspace(-179.5, 179.5, 360),
    ],
    dims=["time", "lat", "lon"],
 )
obs2 = obs2.where(obs2 > 0.6)

fct2 = obs2.copy()
fct2.values = np.random.rand(3, 180, 360)
fct2 = fct2.where(fct2 < 0.25)

# make weights as cosine of the latitude and broadcast
weights = np.cos(np.deg2rad(obs2.lat))
_, weights = xr.broadcast(obs2, weights)
# Remove the time dimension from weights
weights = weights.isel(time=0)

xs.rmse(obs2, fct2, ['lat', 'lon'], weights=weights, skipna=True)

~/anaconda3/envs/py3/lib/python3.7/site-packages/xskillscore/core/np_deterministic.py in _match_nans(a, b, weights)
     37         a[idx], b[idx] = np.nan, np.nan
     38         if weights is not None:
---> 39             weights[idx] = np.nan
     40     return a, b, weights
     41 

ValueError: assignment destination is read-only

[raybellwaves]

Full stack trace

In [8]: xs.rmse(obs2, fct2, ['lat', 'lon'], weights=weights, skipna=True)                                                                    
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-8-922ccbf3baf3> in <module>
----> 1 xs.rmse(obs2, fct2, ['lat', 'lon'], weights=weights, skipna=True)

~/local/bin/anaconda3/envs/xss/lib/python3.6/site-packages/xskillscore/core/deterministic.py in rmse(a, b, dim, weights, skipna)
    632         kwargs={"axis": axis, "skipna": skipna},
    633         dask="parallelized",
--> 634         output_dtypes=[float],
    635     )
    636 

~/local/bin/anaconda3/envs/xss/lib/python3.6/site-packages/xarray/core/computation.py in apply_ufunc(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, meta, *args)
   1062             join=join,
   1063             exclude_dims=exclude_dims,
-> 1064             keep_attrs=keep_attrs,
   1065         )
   1066     elif any(isinstance(a, Variable) for a in args):

~/local/bin/anaconda3/envs/xss/lib/python3.6/site-packages/xarray/core/computation.py in apply_dataarray_vfunc(func, signature, join, exclude_dims, keep_attrs, *args)
    231 
    232     data_vars = [getattr(a, "variable", a) for a in args]
--> 233     result_var = func(*data_vars)
    234 
    235     if signature.num_outputs > 1:

~/local/bin/anaconda3/envs/xss/lib/python3.6/site-packages/xarray/core/computation.py in apply_variable_ufunc(func, signature, exclude_dims, dask, output_dtypes, output_sizes, keep_attrs, meta, *args)
    602                 "apply_ufunc: {}".format(dask)
    603             )
--> 604     result_data = func(*input_data)
    605 
    606     if signature.num_outputs == 1:

~/local/bin/anaconda3/envs/xss/lib/python3.6/site-packages/xskillscore/core/np_deterministic.py in _rmse(a, b, weights, axis, skipna)
    447     sumfunc, meanfunc = _get_numpy_funcs(skipna)
    448     if skipna:
--> 449         a, b, weights = _match_nans(a, b, weights)
    450     weights = _check_weights(weights)
    451 

~/local/bin/anaconda3/envs/xss/lib/python3.6/site-packages/xskillscore/core/np_deterministic.py in _match_nans(a, b, weights)
     37         a[idx], b[idx] = np.nan, np.nan
     38         if weights is not None:
---> 39             weights[idx] = np.nan
     40     return a, b, weights
     41 

ValueError: assignment destination is read-only

[raybellwaves]

Closed via #81

[aaronspring]

I dont understand what that test here checks:

@pytest.fixture
def a_3d():
    da = xr.DataArray(
        np.repeat(np.array([[0, 1, 2], [4, 5, 6], [7, 8, 9]]), 3).reshape(3, 3, 3),
        coords=[
            xr.cftime_range('2000-01-01', '2000-01-03', freq='D'),
            np.linspace(-89.5, 89.5, 3),
            np.linspace(-179.5, 179.5, 3),
        ],
        dims=['time', 'lat', 'lon'],
    )
    return da


@pytest.fixture
def b_3d(a_3d):
    return a_3d.copy()

@pytest.mark.parametrize('metric', WEIGHTED_METRICS)
def test_skipna_broadcast_weights_assignment_destination(
    a_3d, b_3d, weights_lonlat, metric
):
    """Tests that 'assignment destination is read-only' is not raised
    https://github.com/raybellwaves/xskillscore/issues/79"""
    a_3d_nan = a_3d.where(a_3d > 0)
    b_3d_nan = b_3d.where(b_3d > 0)
    res = metric(a_3d_nan, b_3d_nan, ['lat', 'lon'], weights=weights_lonlat, skipna=True)
    assert all([not np.isnan(r) for r in res])

I see here that a metric checks to identical arrays agains each other, which would not make too much sense.

Tried to refactor this in #159