issues

It took some time*, but here is a suggestion to solve option conflicts in xarray.open_dataset().

If any of the options mask_and_scale, decode_times, concat_characters, or decode_coords is manually set and contradicts the manually set choice of decode_cf a ValueError will be raised. This commit requires to change some option default values of open_dataset() parameters from True to None. I hope this is acceptable.

• [x] Closes #3020
• [x] Tests added
• [x] Passes black . && flake8 (mypypasses in principle, but backends/api.py:21 has an unrelated error)
• [x] Fully documented,
• [ ] including whats-new.rst for all changes and api.rst for new API

What do you think? Do I have to add something to whats-new.rst and api.rst?

PS: (*) This is my first PR of this kind and I wanted to build it in a proper testing environment, but I had to set this up first.

Hi,

May I suggest having a default_fillvals option to xarray.open_dataset (and xarray.open_dataarray)?

My problem:

I have netcdf data containing flagged data, that is flagged with the netcdf default fill value of 9.96...e+36. But xarray (0.10.8) only masks arrays that have an explicit fill_value set:

```python import netCDF4, xarray, numpy

nc = netCDF4.Dataset('test.nc', 'w', format='NETCDF4') nc.createDimension('x', 3)

var1 = nc.createVariable('var1', 'f8', ('x',)) var2 = nc.createVariable('var2', 'f8', ('x',), fill_value=netCDF4.default_fillvals['f8'])

var1[:] = numpy.array([0., 1., netCDF4.default_fillvals['f8']]) var2[:] = numpy.array([0., 1., netCDF4.default_fillvals['f8']]) print('netCDF4 var1', nc.variables['var1'][:]) print('netCDF4 var2', nc.variables['var2'][:]) nc.close()

ds = xarray.open_dataset('test.nc') print('xarray var1', ds.var1[:]) print('xarray var2', ds.var2[:]) ```

The problem is, that ds.var1 and ds.var2 are interpreted differently, although netCDF4 shows both as masked: netCDF4 var1 [0.0 1.0 --] netCDF4 var2 [0.0 1.0 --] xarray var1 <xarray.DataArray 'var1' (x: 3)> array([0.00000e+00, 1.00000e+00, 9.96921e+36]) Dimensions without coordinates: x xarray var2 <xarray.DataArray 'var2' (x: 3)> array([ 0., 1., nan]) Dimensions without coordinates: x

I agree, that it is a good default, to mask data, only if the fill_value attribute is set. But I think it would be useful to be able to pass default_fill values to open_dataset to enable reading data, that uses the implicit default values.

What do you think?

Dear all,

I'm trying to plot a vector with bool data. It used to work with xarray version 0.10.7 in an old setup, but it isn't working anymore. Am I doing something wrong or is there something new to consider?

I'm not hundred percent sure, if this problem is due to changes in xarray, numpy or something else

Code example

python import xarray xarray.DataArray([True, False]).plot()

Expected Output

A plot with a line from 1 to 0.

Problem Description

However, I get this error: ``` TypeError Traceback (most recent call last) <ipython-input-22-d911786d1072> in <module> ----> 1 xarray.DataArray([True, False]).plot()

~/python_venvs/python3/py3_18.04/lib/python3.6/site-packages/xarray/plot/plot.py in call(self, kwargs) 463 464 def call(self, kwargs): --> 465 return plot(self._da, **kwargs) 466 467 @functools.wraps(hist)

~/python_venvs/python3/py3_18.04/lib/python3.6/site-packages/xarray/plot/plot.py in plot(darray, row, col, col_wrap, ax, hue, rtol, subplot_kws, kwargs) 200 kwargs["ax"] = ax 201 --> 202 return plotfunc(darray, kwargs) 203 204

~/python_venvs/python3/py3_18.04/lib/python3.6/site-packages/xarray/plot/plot.py in line(darray, row, col, figsize, aspect, size, ax, hue, x, y, xincrease, yincrease, xscale, yscale, xticks, yticks, xlim, ylim, add_legend, _labels, args, kwargs) 321 yplt_val = yplt.values 322 --> 323 _ensure_plottable(xplt_val, yplt_val) 324 325 primitive = ax.plot(xplt_val, yplt_val, args, **kwargs)

~/python_venvs/python3/py3_18.04/lib/python3.6/site-packages/xarray/plot/utils.py in _ensure_plottable(*args) 510 ): 511 raise TypeError( --> 512 "Plotting requires coordinates to be numeric " 513 "or dates of type np.datetime64, " 514 "datetime.datetime, cftime.datetime or "

TypeError: Plotting requires coordinates to be numeric or dates of type np.datetime64, datetime.datetime, cftime.datetime or pd.Interval. ```

Output of xr.show_versions() in the setup that is not working

Output of xr.show_versions() in the setup that was working

as @dcherian said:

matplotlib can plot bool values so we should add that to the check in _ensure_plottable.

• [x] Closes #3722

Dea all,

I encountered a small unforeseen bug using the decode_cf of open_dataset. By only reading the doc string, I was not aware of the complete meaning of this parameter. Especially, that it overwrites other options.

Example: ds = xarray.open_dataset(file_name, mask_and_scale=True, decode_cf=False)

The result is an unmasked and not sclaed dataset. decode_cf simply overwrites other options. See the code: https://github.com/pydata/xarray/blob/stable/xarray/backends/api.py#L308-L312

A simple solution would be to explain, that decode_cf sets mask_and_scale, decode_times, concat_characters, and decode_coords to False. But probably it would be more convenient to detect option conflicts like in my example and raise a ValueError.

What do you think? Do you prefer any of these options? I could write the little PR.