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issue 21

  • CFTimeIndex calendar in repr 13
  • Add histogram method 6
  • Implement multiplication of cftime Tick offsets by floats 6
  • Custom Table when opening GRIB Files 4
  • add freq as CFTimeIndex property and to CFTimeIndex.__repr__ 4
  • Indicate calendar type in CFTimeIndex repr 3
  • bool(Dataset(False)) is True 3
  • Improve performance of xarray.corr() on big datasets 3
  • Visualize task tree 2
  • `xr.infer_freq` month bug for `freq='6MS'` starting Jan becomes `freq='2QS-OCT'` 2
  • `xr.DataArray.plot.pcolormesh(robust="col/row")` 2
  • add average function 1
  • open_mfdataset with proprocess ds[var] 1
  • Implement skipna kwarg in xr.quantile 1
  • expanded HTML repr when opening notebook 1
  • xr.open_dataset(remote_url) file not found 1
  • Calendar utilities 1
  • Use condas dask-core in ci instead of dask to speedup ci and reduce dependencies 1
  • `GHA` `concurrency` 1
  • Feature request: raise more informative error message for `xr.open_dataset(list_of_paths)` 1
  • Should Xarray stop doing automatic index-based alignment? 1

user 1

  • aaronspring · 58 ✖

author_association 1

  • CONTRIBUTOR 58
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1346381256 https://github.com/pydata/xarray/issues/7342#issuecomment-1346381256 https://api.github.com/repos/pydata/xarray/issues/7342 IC_kwDOAMm_X85QQCXI aaronspring 12237157 2022-12-12T12:17:45Z 2022-12-12T12:17:45Z CONTRIBUTOR

Closing in favour of https://github.com/pydata/xarray/issues/7369

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  `xr.DataArray.plot.pcolormesh(robust="col/row")` 1471561942
1336391175 https://github.com/pydata/xarray/issues/7342#issuecomment-1336391175 https://api.github.com/repos/pydata/xarray/issues/7342 IC_kwDOAMm_X85Pp7YH aaronspring 12237157 2022-12-04T11:46:04Z 2022-12-04T11:46:04Z CONTRIBUTOR

True.

So it sounds like what you're hoping for is separate per-column or per-row color scaling?

Exactly.

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  `xr.DataArray.plot.pcolormesh(robust="col/row")` 1471561942
1249758907 https://github.com/pydata/xarray/issues/7045#issuecomment-1249758907 https://api.github.com/repos/pydata/xarray/issues/7045 IC_kwDOAMm_X85Kfc67 aaronspring 12237157 2022-09-16T20:06:21Z 2022-09-16T20:06:21Z CONTRIBUTOR

@shoyer could you maybe provide a code example of the current index aligned behaviour and a future not index aligned behaviour?

I am a bit worried about transitioning previous code bases to such new xarray releases

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  Should Xarray stop doing automatic index-based alignment? 1376109308
1110774460 https://github.com/pydata/xarray/issues/3853#issuecomment-1110774460 https://api.github.com/repos/pydata/xarray/issues/3853 IC_kwDOAMm_X85CNRK8 aaronspring 12237157 2022-04-27T09:24:36Z 2022-04-27T09:24:36Z CONTRIBUTOR

It is possible to set ECCODES_DEFINITION_PATH in eccodes, see http://download.ecmwf.int/test-data/eccodes/html/namespaces.html. But the codetab you want to use here from MPIESM grb output is a CDO parameter table, see https://code.mpimet.mpg.de/projects/cdo/embedded/cdo.pdf#section.1.8, so in my understanding something CDO internal and likely not usable with eccodes/cfgrib.

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  Custom Table when opening GRIB Files 578427969
1110248539 https://github.com/pydata/xarray/issues/6510#issuecomment-1110248539 https://api.github.com/repos/pydata/xarray/issues/6510 IC_kwDOAMm_X85CLQxb aaronspring 12237157 2022-04-26T21:06:04Z 2022-04-26T21:06:04Z CONTRIBUTOR

To be implemented here https://github.com/pydata/xarray/blob/d479009d79374dc4a56c9f4346b1af38f5ac182c/xarray/backends/plugins.py#L102

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  Feature request: raise more informative error message for `xr.open_dataset(list_of_paths)` 1214290591
1037063748 https://github.com/pydata/xarray/pull/6135#issuecomment-1037063748 https://api.github.com/repos/pydata/xarray/issues/6135 IC_kwDOAMm_X8490FZE aaronspring 12237157 2022-02-12T08:28:47Z 2022-02-12T08:28:47Z CONTRIBUTOR

Nice work @aaronspring! I think this is ready to go.

Thank you so much @spencerkclark for your guidance

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  Implement multiplication of cftime Tick offsets by floats 1093466537
1032848596 https://github.com/pydata/xarray/pull/6135#issuecomment-1032848596 https://api.github.com/repos/pydata/xarray/issues/6135 IC_kwDOAMm_X849kATU aaronspring 12237157 2022-02-08T17:03:18Z 2022-02-08T17:03:18Z CONTRIBUTOR

thank you very much for the guidance here. I hope this is now close to how you envisioned this. I merely wanted to get a small improvement in functionality and didnt expect to learn so much. thank you so far @spencerkclark

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  Implement multiplication of cftime Tick offsets by floats 1093466537
1025184642 https://github.com/pydata/xarray/pull/6135#issuecomment-1025184642 https://api.github.com/repos/pydata/xarray/issues/6135 IC_kwDOAMm_X849GxOC aaronspring 12237157 2022-01-30T16:58:23Z 2022-02-01T15:54:29Z CONTRIBUTOR

failing tests are unrelated to cftime IMO

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  Implement multiplication of cftime Tick offsets by floats 1093466537
1025546545 https://github.com/pydata/xarray/pull/6210#issuecomment-1025546545 https://api.github.com/repos/pydata/xarray/issues/6210 IC_kwDOAMm_X849IJkx aaronspring 12237157 2022-01-31T09:40:57Z 2022-01-31T09:40:57Z CONTRIBUTOR

In my understanding we can get rid of fkirc/skip-duplicate-actions and cancel-duplicate-runs.yaml

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  `GHA` `concurrency` 1118564242
1025163440 https://github.com/pydata/xarray/pull/6135#issuecomment-1025163440 https://api.github.com/repos/pydata/xarray/issues/6135 IC_kwDOAMm_X849GsCw aaronspring 12237157 2022-01-30T15:09:52Z 2022-01-30T15:09:52Z CONTRIBUTOR

pre-commit.ci autofix

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  Implement multiplication of cftime Tick offsets by floats 1093466537
1008437041 https://github.com/pydata/xarray/pull/6135#issuecomment-1008437041 https://api.github.com/repos/pydata/xarray/issues/6135 IC_kwDOAMm_X848G4cx aaronspring 12237157 2022-01-09T22:33:03Z 2022-01-09T22:33:03Z CONTRIBUTOR

thanks for the reviews so far @spencerkclark @Illviljan @max-sixty - I think I implemented the suggestions and am looking forward to your next reviews

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  Implement multiplication of cftime Tick offsets by floats 1093466537
1008277351 https://github.com/pydata/xarray/pull/6135#issuecomment-1008277351 https://api.github.com/repos/pydata/xarray/issues/6135 IC_kwDOAMm_X848GRdn aaronspring 12237157 2022-01-09T11:13:01Z 2022-01-09T11:13:01Z CONTRIBUTOR

Would you remove the isinstance checks? I though that mypy does check at runtime, so it would detect a wrong input by the user. (I am still new to typing etc)

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  Implement multiplication of cftime Tick offsets by floats 1093466537
985942042 https://github.com/pydata/xarray/issues/6045#issuecomment-985942042 https://api.github.com/repos/pydata/xarray/issues/6045 IC_kwDOAMm_X846xEga aaronspring 12237157 2021-12-04T01:37:16Z 2021-12-04T03:02:12Z CONTRIBUTOR

code in xarray is nearly identical to pandas. Maybe I misunderstood the documentation/explanation, i.e. meaning of month in freq-month for seasonal

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  `xr.infer_freq` month bug for `freq='6MS'` starting Jan becomes `freq='2QS-OCT'` 1071049280
985925827 https://github.com/pydata/xarray/issues/6045#issuecomment-985925827 https://api.github.com/repos/pydata/xarray/issues/6045 IC_kwDOAMm_X846xAjD aaronspring 12237157 2021-12-04T00:22:47Z 2021-12-04T00:22:47Z CONTRIBUTOR

the same happens also in pandas... ```python import pandas as pd i_pd = pd.date_range(start="2000-01-01", end="2002-01-01", freq="6MS") i_pd DatetimeIndex(['2000-01-01', '2000-07-01', '2001-01-01', '2001-07-01', '2002-01-01'], dtype='datetime64[ns]', freq='6MS')

pd.infer_freq(i_pd) '2QS-OCT' ```

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  `xr.infer_freq` month bug for `freq='6MS'` starting Jan becomes `freq='2QS-OCT'` 1071049280
977396964 https://github.com/pydata/xarray/pull/6007#issuecomment-977396964 https://api.github.com/repos/pydata/xarray/issues/6007 IC_kwDOAMm_X846QeTk aaronspring 12237157 2021-11-24T02:05:42Z 2021-11-24T02:05:42Z CONTRIBUTOR

bokeh etc not installed anymore when temporarily not installing iris from conda https://github.com/pydata/xarray/runs/4298565586?check_suite_focus=true

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  Use condas dask-core in ci instead of dask to speedup ci and reduce dependencies 1058047751
853138609 https://github.com/pydata/xarray/issues/4610#issuecomment-853138609 https://api.github.com/repos/pydata/xarray/issues/4610 MDEyOklzc3VlQ29tbWVudDg1MzEzODYwOQ== aaronspring 12237157 2021-06-02T15:45:45Z 2021-06-02T15:45:45Z CONTRIBUTOR

This makes sense, but it sounds like this suggestion (of accepting Datasets not just DataArrays) is mostly a convenience tool for applying histograms to particular variables across multiple datasets quickly. It's not fundamentally different to picking and choosing the variables you want from multiple datasets and feeding them in to histogram as dataarrays.

agree.

I think we should focus on including features that enable analyses that would otherwise be difficult or impossible, for example ND bins

looking forward to the PR

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  Add histogram method 750985364
852944667 https://github.com/pydata/xarray/issues/4610#issuecomment-852944667 https://api.github.com/repos/pydata/xarray/issues/4610 MDEyOklzc3VlQ29tbWVudDg1Mjk0NDY2Nw== aaronspring 12237157 2021-06-02T11:22:07Z 2021-06-02T11:22:07Z CONTRIBUTOR

I like your explanation of the two different inputs @dougiesquire and for multi-dim datasets these must be xr.datasets. my point about the bins is that if the inputs are two xr.datasets, then also the bins should be two xr.datasets. If the bins were only two xr.Arrays, then how could these bins discriminate for the different variables in the inputs?

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  Add histogram method 750985364
852428526 https://github.com/pydata/xarray/issues/4610#issuecomment-852428526 https://api.github.com/repos/pydata/xarray/issues/4610 MDEyOklzc3VlQ29tbWVudDg1MjQyODUyNg== aaronspring 12237157 2021-06-01T20:36:25Z 2021-06-01T20:36:25Z CONTRIBUTOR

I am unsure about this and cannot manage to put my Südasien down precisely.

Calculating a contingency table for instance between two multivar inputs:

ˋˋˋ xhistogram(ds_observations_multivar, ds_forecast_multivar, bins=[ds_obs_multivar_edges, ds_forecast_multivar_edges ]) ˋˋˋ

as in https://github.com/xarray-contrib/xskillscore/blob/6f7be06098eefa1cdb90f7319f577c274621301c/xskillscore/core/contingency.py#L156

maybe @dougiesquire can phrase this more precisely

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  Add histogram method 750985364
852364749 https://github.com/pydata/xarray/issues/4610#issuecomment-852364749 https://api.github.com/repos/pydata/xarray/issues/4610 MDEyOklzc3VlQ29tbWVudDg1MjM2NDc0OQ== aaronspring 12237157 2021-06-01T18:51:47Z 2021-06-01T18:51:47Z CONTRIBUTOR

What I'm unclear about is what you want to achieve by inputting an xarray.Dataset that couldn't be done with inputs of ND xr.DataArrays as both data and bins?

with dataset bins I want to have different bin_edges for each dataset. If bins is only a dataArray, I cannot have this. Can I?

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  Add histogram method 750985364
852231700 https://github.com/pydata/xarray/issues/4610#issuecomment-852231700 https://api.github.com/repos/pydata/xarray/issues/4610 MDEyOklzc3VlQ29tbWVudDg1MjIzMTcwMA== aaronspring 12237157 2021-06-01T15:45:00Z 2021-06-01T15:45:00Z CONTRIBUTOR

I tried to show in https://gist.github.com/aaronspring/251553f132202cc91aadde03f2a452f9 how I would like to use xr.Datasets as bins, e.g. defining bin edges based on quantiles of the climatology, i.e. bin edges depend on lon, lat, maybe weekofyear and variable.

I tried show in the gist that I could be also nice to allow xr.Datasets as bins if the inputs are xr.Datasets.

You can already choose different bins to use for each input variable`

I cannot find this in #5400. I should checkout and run the code locally.

Yep, the example xskillscore code posted doesnt allow nd bins. forgot that. correct. in my head thinking about the future it does. https://github.com/xarray-contrib/xskillscore/blob/6f7be06098eefa1cdb90f7319f577c274621301c/xskillscore/core/probabilistic.py#L498 takes xr.Datasets as bins and in a previous version we used xhist but then changed to make this run on nd arrays and xr.Datasets.

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  Add histogram method 750985364
852120100 https://github.com/pydata/xarray/issues/4610#issuecomment-852120100 https://api.github.com/repos/pydata/xarray/issues/4610 MDEyOklzc3VlQ29tbWVudDg1MjEyMDEwMA== aaronspring 12237157 2021-06-01T13:22:25Z 2021-06-01T13:24:19Z CONTRIBUTOR

what about a list of xarray.Datasets as bins? suppose you have an xr.Dataset you want to bin different variables for different bins (eg from xr.Dataset.quantile)

@dougiesquire implemented this in https://github.com/xarray-contrib/xskillscore/blob/2217b58c536ec1b3d2c42265ed6689a740c2b3bf/xskillscore/core/utils.py#L133

EDIT: seeing now that this issue and #5400 aims to implement xr.DataArray.hist only. xr.Dataset would be also nice :)

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  Add histogram method 750985364
819566971 https://github.com/pydata/xarray/issues/5155#issuecomment-819566971 https://api.github.com/repos/pydata/xarray/issues/5155 MDEyOklzc3VlQ29tbWVudDgxOTU2Njk3MQ== aaronspring 12237157 2021-04-14T14:34:55Z 2021-04-14T14:34:55Z CONTRIBUTOR
  1. exists as ds.time.to_index().calendar
  2. would like to use
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  Calendar utilities 857947050
760025539 https://github.com/pydata/xarray/issues/4804#issuecomment-760025539 https://api.github.com/repos/pydata/xarray/issues/4804 MDEyOklzc3VlQ29tbWVudDc2MDAyNTUzOQ== aaronspring 12237157 2021-01-14T08:44:22Z 2021-01-14T08:44:22Z CONTRIBUTOR

Thanks for the suggestion with xr.align.

my speculation is that xs.pearson_r is a bit faster because we first write the whole function in numpy and then pass it through xr.apply_ufunc. I think therefore it only works for xr but not dask.da

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  Improve performance of xarray.corr() on big datasets 785329941
759767957 https://github.com/pydata/xarray/issues/4804#issuecomment-759767957 https://api.github.com/repos/pydata/xarray/issues/4804 MDEyOklzc3VlQ29tbWVudDc1OTc2Nzk1Nw== aaronspring 12237157 2021-01-13T22:04:38Z 2021-01-13T22:04:38Z CONTRIBUTOR

Your function from the notebook could also easily implement the builtin weighted function

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  Improve performance of xarray.corr() on big datasets 785329941
759766466 https://github.com/pydata/xarray/issues/4804#issuecomment-759766466 https://api.github.com/repos/pydata/xarray/issues/4804 MDEyOklzc3VlQ29tbWVudDc1OTc2NjQ2Ng== aaronspring 12237157 2021-01-13T22:01:49Z 2021-01-13T22:01:49Z CONTRIBUTOR

We implemented xr.corr as xr.pearson_r in https://xskillscore.readthedocs.io/en/stable/api/xskillscore.pearson_r.html#xskillscore.pearson_r and it’s ~30% faster than xr.corr see #4768

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  Improve performance of xarray.corr() on big datasets 785329941
733575449 https://github.com/pydata/xarray/pull/4597#issuecomment-733575449 https://api.github.com/repos/pydata/xarray/issues/4597 MDEyOklzc3VlQ29tbWVudDczMzU3NTQ0OQ== aaronspring 12237157 2020-11-25T09:16:49Z 2020-11-25T09:16:49Z CONTRIBUTOR

Thanks for the smooth review process @spencerkclark @keewis

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  add freq as CFTimeIndex property and to CFTimeIndex.__repr__ 748094631
731725142 https://github.com/pydata/xarray/pull/4597#issuecomment-731725142 https://api.github.com/repos/pydata/xarray/issues/4597 MDEyOklzc3VlQ29tbWVudDczMTcyNTE0Mg== aaronspring 12237157 2020-11-22T10:11:53Z 2020-11-22T10:11:53Z CONTRIBUTOR

Ah I need to account for the docstring examples with only one or two items, maybe dropping freq then

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  add freq as CFTimeIndex property and to CFTimeIndex.__repr__ 748094631
731643425 https://github.com/pydata/xarray/pull/4597#issuecomment-731643425 https://api.github.com/repos/pydata/xarray/issues/4597 MDEyOklzc3VlQ29tbWVudDczMTY0MzQyNQ== aaronspring 12237157 2020-11-21T22:04:11Z 2020-11-21T22:04:11Z CONTRIBUTOR

also should it be frequency or freq?

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  add freq as CFTimeIndex property and to CFTimeIndex.__repr__ 748094631
731637045 https://github.com/pydata/xarray/pull/4597#issuecomment-731637045 https://api.github.com/repos/pydata/xarray/issues/4597 MDEyOklzc3VlQ29tbWVudDczMTYzNzA0NQ== aaronspring 12237157 2020-11-21T21:10:44Z 2020-11-21T21:10:44Z CONTRIBUTOR

I also get this error locally. somehow in some envs xarray (but not in others) tries to use daysinmonth. I also know about days_in_month, but just changing that in frequencies.py https://github.com/pydata/xarray/blob/d9ebcafaddf0bb80052d30f43ca5ea18a5c7229f/xarray/coding/frequencies.py#L261 didnt help it.

``` ____________ test_cftimeindex_freq_in_repr[MS-noleap] _______________

freq = 'MS', calendar = 'noleap'

@requires_cftime
@pytest.mark.parametrize("calendar", ["noleap", "360_day"])
@pytest.mark.parametrize("freq", ["1D", "MS"])
def test_cftimeindex_freq_in_repr(freq,calendar):
    index = xr.cftime_range(start="2000", periods=3, freq=freq, calendar=calendar)
  assert f', freq={freq}' in index.__repr__()

/Users/aaron.spring/Coding/xarray/xarray/tests/test_cftimeindex.py:952:


/Users/aaron.spring/Coding/xarray/xarray/coding/cftimeindex.py:342: in repr attrs_str = format_attrs(self) /Users/aaron.spring/Coding/xarray/xarray/coding/cftimeindex.py:263: in format_attrs "freq": f"'{index.freq}'" /Users/aaron.spring/Coding/xarray/xarray/coding/cftimeindex.py:691: in freq return infer_freq(self) /Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:97: in infer_freq return inferer.get_freq() /Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:132: in get_freq return self._infer_daily_rule() /Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:165: in _infer_daily_rule monthly_rule = self._get_monthly_rule() /Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:199: in _get_monthly_rule return {"cs": "MS", "ce": "M"}.get(month_anchor_check(self.index))


dates = <[AttributeError("'cftime._cftime.DatetimeNoLeap' object has no attribute 'daysinmonth'",) raised in repr()] CFTimeIndex object at 0x7fca9312b160>

def month_anchor_check(dates):
    """Return the monthly offset string.

    Return "cs" if all dates are the first days of the month,
    "ce" if all dates are the last day of the month,
    None otherwise.

    Replicated pandas._libs.tslibs.resolution.month_position_check
    but without business offset handling.
    """
    calendar_end = True
    calendar_start = True

    for date in dates:
        if calendar_start:
            calendar_start &= date.day == 1

        if calendar_end:
          cal = date.day == date.daysinmonth

E AttributeError: 'cftime._cftime.DatetimeNoLeap' object has no attribute 'daysinmonth'

/Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:261: AttributeError ____________ test_cftimeindex_freq_in_repr[MS-360_day] ______________

freq = 'MS', calendar = '360_day'

@requires_cftime
@pytest.mark.parametrize("calendar", ["noleap", "360_day"])
@pytest.mark.parametrize("freq", ["1D", "MS"])
def test_cftimeindex_freq_in_repr(freq,calendar):
    index = xr.cftime_range(start="2000", periods=3, freq=freq, calendar=calendar)
  assert f', freq={freq}' in index.__repr__()

/Users/aaron.spring/Coding/xarray/xarray/tests/test_cftimeindex.py:952:


/Users/aaron.spring/Coding/xarray/xarray/coding/cftimeindex.py:342: in repr attrs_str = format_attrs(self) /Users/aaron.spring/Coding/xarray/xarray/coding/cftimeindex.py:263: in format_attrs "freq": f"'{index.freq}'" /Users/aaron.spring/Coding/xarray/xarray/coding/cftimeindex.py:691: in freq return infer_freq(self) /Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:97: in infer_freq return inferer.get_freq() /Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:132: in get_freq return self._infer_daily_rule() /Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:165: in _infer_daily_rule monthly_rule = self._get_monthly_rule() /Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:199: in _get_monthly_rule return {"cs": "MS", "ce": "M"}.get(month_anchor_check(self.index))


dates = <[AttributeError("'cftime._cftime.Datetime360Day' object has no attribute 'daysinmonth'",) raised in repr()] CFTimeIndex object at 0x7fca930cfe10>

def month_anchor_check(dates):
    """Return the monthly offset string.

    Return "cs" if all dates are the first days of the month,
    "ce" if all dates are the last day of the month,
    None otherwise.

    Replicated pandas._libs.tslibs.resolution.month_position_check
    but without business offset handling.
    """
    calendar_end = True
    calendar_start = True

    for date in dates:
        if calendar_start:
            calendar_start &= date.day == 1

        if calendar_end:
          cal = date.day == date.daysinmonth

E AttributeError: 'cftime._cftime.Datetime360Day' object has no attribute 'daysinmonth'

/Users/aaron.spring/Coding/xarray/xarray/coding/frequencies.py:261: AttributeError ===================================================================================== short test summary info ===================================================================================== FAILED xarray/tests/test_cftimeindex.py::test_cftimeindex_freq_in_repr[1D-noleap] - AttributeError: 'cftime._cftime.DatetimeNoLeap' object has no attribute 'daysinmonth' FAILED xarray/tests/test_cftimeindex.py::test_cftimeindex_freq_in_repr[1D-360_day] - AttributeError: 'cftime._cftime.Datetime360Day' object has no attribute 'daysinmonth' FAILED xarray/tests/test_cftimeindex.py::test_cftimeindex_freq_in_repr[MS-noleap] - AttributeError: 'cftime._cftime.DatetimeNoLeap' object has no attribute 'daysinmonth' FAILED xarray/tests/test_cftimeindex.py::test_cftimeindex_freq_in_repr[MS-360_day] - AttributeError: 'cftime._cftime.Datetime360Day' object has no attribute 'daysinmonth' ======================================================================================== 4 failed in 2.58s =========================================================================== ```

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  add freq as CFTimeIndex property and to CFTimeIndex.__repr__ 748094631
730427143 https://github.com/pydata/xarray/issues/2416#issuecomment-730427143 https://api.github.com/repos/pydata/xarray/issues/2416 MDEyOklzc3VlQ29tbWVudDczMDQyNzE0Mw== aaronspring 12237157 2020-11-19T14:53:08Z 2020-11-19T14:53:08Z CONTRIBUTOR

using this feature now alot. @spencerkclark what about implementing also freq into the CFTimeIndex repr?

Its hard to see the frequency by eye sometimes, I would just rely on xr.infer_freq and add to the repr str, also if freq is None/indistinguishable

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  Indicate calendar type in CFTimeIndex repr 360420464
697302214 https://github.com/pydata/xarray/issues/4451#issuecomment-697302214 https://api.github.com/repos/pydata/xarray/issues/4451 MDEyOklzc3VlQ29tbWVudDY5NzMwMjIxNA== aaronspring 12237157 2020-09-23T11:25:58Z 2020-09-23T11:25:58Z CONTRIBUTOR

cross posted: https://github.com/Unidata/netcdf4-python/issues/1043

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  xr.open_dataset(remote_url) file not found 707223289
669204458 https://github.com/pydata/xarray/issues/4290#issuecomment-669204458 https://api.github.com/repos/pydata/xarray/issues/4290 MDEyOklzc3VlQ29tbWVudDY2OTIwNDQ1OA== aaronspring 12237157 2020-08-05T13:48:55Z 2020-08-05T13:48:55Z CONTRIBUTOR

For those who think bool(xr.Dataset(dict(x=False))) should evaluate to False, what do you think dict(x=False) should evaluate to?

good point

IIUC, this is somewhat of an edge case — it's only possible to coerce DataArray to bool when there's exactly one element. (Not that we shouldn't resolve)

I now understand the underlying problem better with your comments. My expectations were too naive about it. I cannot evaluate the consequences of changing this. I close this issue and hopefully users having this problem in the future will find this issue.

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  bool(Dataset(False)) is True 668717850
666380379 https://github.com/pydata/xarray/issues/4290#issuecomment-666380379 https://api.github.com/repos/pydata/xarray/issues/4290 MDEyOklzc3VlQ29tbWVudDY2NjM4MDM3OQ== aaronspring 12237157 2020-07-30T13:56:30Z 2020-07-30T14:13:24Z CONTRIBUTOR

currently

python if (xrobject > 10).any(): raise ValueError('blabla') depends on whether xrobject is xr.DataArray or xr.Dataset.

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  bool(Dataset(False)) is True 668717850
666370889 https://github.com/pydata/xarray/issues/4290#issuecomment-666370889 https://api.github.com/repos/pydata/xarray/issues/4290 MDEyOklzc3VlQ29tbWVudDY2NjM3MDg4OQ== aaronspring 12237157 2020-07-30T13:39:55Z 2020-07-30T13:39:55Z CONTRIBUTOR

thanks for the explanation. but from a naive user perspective,

python bool(xr.DataArray(False).to_dataset(name='var')) # False bool(xr.DataArray(True).to_dataset(name='var')) # True bool(xr.DataArray(False)) # False bool(xr.DataArray(True)) # True would be nice.

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  bool(Dataset(False)) is True 668717850
663138597 https://github.com/pydata/xarray/pull/4092#issuecomment-663138597 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY2MzEzODU5Nw== aaronspring 12237157 2020-07-23T17:36:56Z 2020-07-23T17:38:38Z CONTRIBUTOR

My pleasure. Learnt a lot.

And it was a long-standing issue that was mentioned in a medium article about xarray looking for more contributors.

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  CFTimeIndex calendar in repr 624378150
660531286 https://github.com/pydata/xarray/pull/4092#issuecomment-660531286 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY2MDUzMTI4Ng== aaronspring 12237157 2020-07-18T19:34:29Z 2020-07-18T19:34:29Z CONTRIBUTOR

Thanks @aaronspring; this is looking very close! Just a few more minor suggestions.

I hope this is the final one. all tests pass. implemented your suggestions. took me a few commits, but I learned a lot. thanks for the guidance @spencerkclark

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  CFTimeIndex calendar in repr 624378150
656101309 https://github.com/pydata/xarray/pull/4092#issuecomment-656101309 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY1NjEwMTMwOQ== aaronspring 12237157 2020-07-09T12:35:49Z 2020-07-09T12:35:49Z CONTRIBUTOR

dont understand why isort fails

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  CFTimeIndex calendar in repr 624378150
654743050 https://github.com/pydata/xarray/pull/4092#issuecomment-654743050 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY1NDc0MzA1MA== aaronspring 12237157 2020-07-07T10:00:18Z 2020-07-07T10:00:18Z CONTRIBUTOR

now aligns to display_width:

python for dw in [40,60,80,120]: with xr.set_options(display_width=dw): print(time[:2],dw,'\n')

``` CFTimeIndex([2000-01-01 00:00:00, 2000-01-02 00:00:00], dtype='object', length=2, calendar='gregorian') 40

CFTimeIndex([2000-01-01 00:00:00, 2000-01-02 00:00:00], dtype='object', length=2, calendar='gregorian') 60

CFTimeIndex([2000-01-01 00:00:00, 2000-01-02 00:00:00], dtype='object', length=2, calendar='gregorian') 80

CFTimeIndex([2000-01-01 00:00:00, 2000-01-02 00:00:00], dtype='object', length=2, calendar='gregorian') 120 ```

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  CFTimeIndex calendar in repr 624378150
653742478 https://github.com/pydata/xarray/pull/4092#issuecomment-653742478 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY1Mzc0MjQ3OA== aaronspring 12237157 2020-07-04T09:10:57Z 2020-07-04T09:10:57Z CONTRIBUTOR

@spencerkclark I reimplemented the repr. Mostly went after the visuals. So now this looks like before but including calendar in the repr. Any more tests needed? Would you please give this a look?

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  CFTimeIndex calendar in repr 624378150
644035565 https://github.com/pydata/xarray/pull/4092#issuecomment-644035565 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY0NDAzNTU2NQ== aaronspring 12237157 2020-06-15T10:08:21Z 2020-06-15T10:08:21Z CONTRIBUTOR

I now reimplemented the visuals of pd.Index and also test against pd.Index.repr @spencerkclark

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  CFTimeIndex calendar in repr 624378150
641182167 https://github.com/pydata/xarray/pull/4092#issuecomment-641182167 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY0MTE4MjE2Nw== aaronspring 12237157 2020-06-09T10:02:20Z 2020-06-09T15:31:03Z CONTRIBUTOR

now after clicking on the data item:

this PR is now ready for review. I don't understand why azure tests are failing.

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  CFTimeIndex calendar in repr 624378150
640096726 https://github.com/pydata/xarray/pull/4092#issuecomment-640096726 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY0MDA5NjcyNg== aaronspring 12237157 2020-06-06T17:59:49Z 2020-06-06T23:22:20Z CONTRIBUTOR

I found a workaround with to_index() in formatting.short_data_repr. this is makes one test fail: xarray/tests/test_dask.py TestDataArrayAndDataset.test_dataarray_repr. is this ok or not a valid way to implement a cftimeindex.repr?

EDIT: I ensure now that to_index is only done when if CFTimeIndex.

Ready for review.

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  CFTimeIndex calendar in repr 624378150
640073445 https://github.com/pydata/xarray/pull/4092#issuecomment-640073445 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDY0MDA3MzQ0NQ== aaronspring 12237157 2020-06-06T14:54:31Z 2020-06-06T14:54:31Z CONTRIBUTOR

Currently only the cftimeindex repr shows the calendar property. I aim to get it into the dataset/dataarray repr.

would it be a good idea to modify formatting.py.array_repr(array)? IndexVariable uses this repr. Once time is a coordinate, it becomes an IndexVariable. but the index variable doesnt have this cftime.calender property anymore. Should I try to add this calendar property to the array or would this not be desired?

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  CFTimeIndex calendar in repr 624378150
638913996 https://github.com/pydata/xarray/pull/4092#issuecomment-638913996 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDYzODkxMzk5Ng== aaronspring 12237157 2020-06-04T15:10:46Z 2020-06-04T15:10:46Z CONTRIBUTOR

I do understand the meaning of this last sentence @spencerkclark

My sense is that it is more important that indexes with the same date type have the same calendar attribute than that the calendar argument passed to cftime_range is propagated verbatim to the index it produces. What do you think?

Should I rather test on cftimeindex created in a different way?

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  CFTimeIndex calendar in repr 624378150
638779099 https://github.com/pydata/xarray/pull/4092#issuecomment-638779099 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDYzODc3OTA5OQ== aaronspring 12237157 2020-06-04T11:02:00Z 2020-06-04T11:02:00Z CONTRIBUTOR

This doesnt change the html repr yet: when clicking on the data symbol, calendar is not shown in the printout. I will further try to fix this

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  CFTimeIndex calendar in repr 624378150
638302372 https://github.com/pydata/xarray/pull/4092#issuecomment-638302372 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDYzODMwMjM3Mg== aaronspring 12237157 2020-06-03T16:17:01Z 2020-06-03T16:17:01Z CONTRIBUTOR

I was hoping to inherit from pandas like: python def __repr__(self): super().__repr__() return self.__repr__().strip(")")+f", calendar={self.calendar}')"

But I will now try to rebuild as in pandas.

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  CFTimeIndex calendar in repr 624378150
637369697 https://github.com/pydata/xarray/pull/4092#issuecomment-637369697 https://api.github.com/repos/pydata/xarray/issues/4092 MDEyOklzc3VlQ29tbWVudDYzNzM2OTY5Nw== aaronspring 12237157 2020-06-02T08:10:24Z 2020-06-02T08:10:24Z CONTRIBUTOR

how should I extend the __repr__ coming from pd.Index

if you define a __repr__ method under CFTimeIndex, won't it override pd.Index.__repr__?

Yes. I will do that. My question was whether should replicate the pd.Index.repr or try to import or inherit as much as I can from pandas?

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  CFTimeIndex calendar in repr 624378150
625720635 https://github.com/pydata/xarray/issues/4025#issuecomment-625720635 https://api.github.com/repos/pydata/xarray/issues/4025 MDEyOklzc3VlQ29tbWVudDYyNTcyMDYzNQ== aaronspring 12237157 2020-05-08T09:10:08Z 2020-05-08T09:10:08Z CONTRIBUTOR

also works: da.data.visualize()

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  Visualize task tree 611839345
624905520 https://github.com/pydata/xarray/issues/4041#issuecomment-624905520 https://api.github.com/repos/pydata/xarray/issues/4041 MDEyOklzc3VlQ29tbWVudDYyNDkwNTUyMA== aaronspring 12237157 2020-05-06T21:39:55Z 2020-05-06T21:39:55Z CONTRIBUTOR

me too on Firefox linux

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  expanded HTML repr when opening notebook 613579881
623506526 https://github.com/pydata/xarray/issues/4025#issuecomment-623506526 https://api.github.com/repos/pydata/xarray/issues/4025 MDEyOklzc3VlQ29tbWVudDYyMzUwNjUyNg== aaronspring 12237157 2020-05-04T14:43:25Z 2020-05-04T14:43:25Z CONTRIBUTOR

this is great. thanks for the hint.

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  Visualize task tree 611839345
598193427 https://github.com/pydata/xarray/issues/2416#issuecomment-598193427 https://api.github.com/repos/pydata/xarray/issues/2416 MDEyOklzc3VlQ29tbWVudDU5ODE5MzQyNw== aaronspring 12237157 2020-03-12T13:44:45Z 2020-03-12T13:44:45Z CONTRIBUTOR

would this be a starting point: https://github.com/pydata/xarray/blob/603b0ad3f8a02a9e1180eb8dfc72f7f885f0e19a/xarray/core/variable.py#L2222 ? but I dont see where calendar is coming from.

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  Indicate calendar type in CFTimeIndex repr 360420464
598191749 https://github.com/pydata/xarray/issues/2416#issuecomment-598191749 https://api.github.com/repos/pydata/xarray/issues/2416 MDEyOklzc3VlQ29tbWVudDU5ODE5MTc0OQ== aaronspring 12237157 2020-03-12T13:41:13Z 2020-03-12T13:41:13Z CONTRIBUTOR

such a calendar attribute would be nice. Didnt find a workaround. My goal is to get a str for calendar type from ds:

Once implemented, this could then be accessed via ds.time.to_index().calendar. with some help where to start I would go for this.

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  Indicate calendar type in CFTimeIndex repr 360420464
598035966 https://github.com/pydata/xarray/issues/3853#issuecomment-598035966 https://api.github.com/repos/pydata/xarray/issues/3853 MDEyOklzc3VlQ29tbWVudDU5ODAzNTk2Ng== aaronspring 12237157 2020-03-12T06:58:55Z 2020-03-12T06:58:55Z CONTRIBUTOR

This was my workaround. https://github.com/aaronspring/pymistral/issues/19

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  Custom Table when opening GRIB Files 578427969
598031406 https://github.com/pydata/xarray/issues/3853#issuecomment-598031406 https://api.github.com/repos/pydata/xarray/issues/3853 MDEyOklzc3VlQ29tbWVudDU5ODAzMTQwNg== aaronspring 12237157 2020-03-12T06:41:40Z 2020-03-12T06:41:40Z CONTRIBUTOR

I would use it with the echam6 and jsbach ‘.codes’ files in MPIESM.

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  Custom Table when opening GRIB Files 578427969
597939300 https://github.com/pydata/xarray/issues/3853#issuecomment-597939300 https://api.github.com/repos/pydata/xarray/issues/3853 MDEyOklzc3VlQ29tbWVudDU5NzkzOTMwMA== aaronspring 12237157 2020-03-12T00:02:35Z 2020-03-12T00:02:35Z CONTRIBUTOR

I would love that feature. Also found that pyngl docu but didn’t get it working...

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  Custom Table when opening GRIB Files 578427969
596072003 https://github.com/pydata/xarray/pull/3844#issuecomment-596072003 https://api.github.com/repos/pydata/xarray/issues/3844 MDEyOklzc3VlQ29tbWVudDU5NjA3MjAwMw== aaronspring 12237157 2020-03-07T10:25:18Z 2020-03-07T10:25:18Z CONTRIBUTOR

I am unsure whether I added enough tests. only one test that checks for different values with or without skipna.

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  Implement skipna kwarg in xr.quantile 577105538
485444538 https://github.com/pydata/xarray/issues/422#issuecomment-485444538 https://api.github.com/repos/pydata/xarray/issues/422 MDEyOklzc3VlQ29tbWVudDQ4NTQ0NDUzOA== aaronspring 12237157 2019-04-22T15:09:16Z 2019-04-22T15:09:16Z CONTRIBUTOR

Can the stats functions from https://esmlab.readthedocs.io/en/latest/api.html#statistics-functions be used?

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  add average function 84127296
483738391 https://github.com/pydata/xarray/issues/2900#issuecomment-483738391 https://api.github.com/repos/pydata/xarray/issues/2900 MDEyOklzc3VlQ29tbWVudDQ4MzczODM5MQ== aaronspring 12237157 2019-04-16T16:38:47Z 2019-04-16T16:38:47Z CONTRIBUTOR

thanks @dcherian that was easier than expected. it speeds up a bit but not much. thanks

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  open_mfdataset with proprocess ds[var] 433833707

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