issues

MCVE Code Sample

```python loc,scale,shape = da.rolling(time=59).reduce(scipy.stats.skewnorm)

```

Expected Output

python-traceback Traceback (most recent call last): File "<input>", line 1, in <module> File "/Users/mada0007/anaconda3/envs/modes/lib/python3.7/site-packages/xarray/core/rolling.py", line 217, in reduce result = windows.reduce(func, dim=rolling_dim, **kwargs) File "/Users/mada0007/anaconda3/envs/modes/lib/python3.7/site-packages/xarray/core/dataarray.py", line 1636, in reduce var = self.variable.reduce(func, dim, axis, keep_attrs, **kwargs) File "/Users/mada0007/anaconda3/envs/modes/lib/python3.7/site-packages/xarray/core/variable.py", line 1371, in reduce data = func(input_data, axis=axis, **kwargs) File "/Users/mada0007/anaconda3/envs/modes/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 770, in __call__ return self.freeze(*args, **kwds) File "/Users/mada0007/anaconda3/envs/modes/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 767, in freeze return rv_frozen(self, *args, **kwds) File "/Users/mada0007/anaconda3/envs/modes/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 435, in __init__ shapes, _, _ = self.dist._parse_args(*args, **kwds) TypeError: _parse_args() got an unexpected keyword argument 'axis'

Output of ``ommit: None

python: 3.7.2 (default, Dec 29 2018, 00:00:04) [Clang 4.0.1 (tags/RELEASE_401/final)] python-bits: 64 OS: Darwin OS-release: 18.2.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: en_AU.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.2 xarray: 0.12.1 pandas: 0.24.2 numpy: 1.15.4 scipy: 1.2.1 netCDF4: 1.5.1.2 pydap: installed h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.0.3.4 nc_time_axis: None PseudonetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 1.2.2 distributed: 1.28.1 matplotlib: 3.0.3 cartopy: 0.17.0 seaborn: 0.9.0 setuptools: 40.8.0 pip: 19.0.3 conda: None pytest: None IPython: None sphinx: None``

How can I please make this code work?

I have array of monthy data. I want to select monthly values starting from october to march like this my data = starts from [1950-01,1950-02,1950-03, ...]

this is what I want selection = [1950-10, 1950-11, 1950-12, 1960-1,1960-2, 1960-3, ...] # notice it continues to 1960

thanks

I am looking for how to apply xarray rolling window to this function. I have really searched a lot but my effort is still futile..

My data is xarray data of shape (time, lon, lat) (323x180x360) respectively

```python def get_grps(s,axis=0, thresh=-1, Nmin=2): """ Nmin : int > 0 Min number of consecutive values below threshold. """ s = pd.Series(s) m = np.logical_and.reduce([s.shift(-i).le(thresh) for i in range(Nmin)]) if Nmin > 1: m = pd.Series(m, index=s.index).replace({False: np.NaN}).ffill(limit=Nmin-1).fillna(False) else: m = pd.Series(m, index=s.index)

# Form consecutive groups
gps = m.ne(m.shift(1)).cumsum().where(m)

# Return None if no groups, else the aggregations
if gps.isnull().all():
    return [0]
else:
    d = s.groupby(gps).agg([list, sum, 'size']).reset_index(drop=True)

    data = len((d['sum']))  ### returning frequency

    data = np.array(data)
    return (data)

```

I tried this

python spi = xr.DataArray(dims=("time", "lon", "lat"), data=np.random.randn(324, 180, 360)) spi.rolling(time=59).reduce(get_grps)

I get this error

python Traceback (most recent call last): File "<input>", line 1, in <module> File "/Users/mada0007/anaconda3/envs/RESEARCH_QUESTION_TWO/lib/python3.7/site-packages/xarray/core/rolling.py", line 287, in reduce result = windows.reduce(func, dim=rolling_dim, **kwargs) File "/Users/mada0007/anaconda3/envs/RESEARCH_QUESTION_TWO/lib/python3.7/site-packages/xarray/core/dataarray.py", line 2216, in reduce var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs) File "/Users/mada0007/anaconda3/envs/RESEARCH_QUESTION_TWO/lib/python3.7/site-packages/xarray/core/variable.py", line 1529, in reduce data = func(input_data, axis=axis, **kwargs) File "<input>", line 7, in get_grps File "/Users/mada0007/anaconda3/envs/RESEARCH_QUESTION_TWO/lib/python3.7/site-packages/pandas/core/series.py", line 314, in __init__ data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True) File "/Users/mada0007/anaconda3/envs/RESEARCH_QUESTION_TWO/lib/python3.7/site-packages/pandas/core/internals/construction.py", line 730, in sanitize_array raise Exception("Data must be 1-dimensional") Exception: Data must be 1-dimensional

How can I rectify this?

Thanks

I am trying to apply ufunc to my code to speed it up. Currently I am looping over lon and lat and it takes ages. After long reads I came up with this though am still not sure where I a going wrong. Suggestions and Ideas would be very helpful to get me going. thanks

``` python def get_grps(s, thresh=-1, Nmin=3): """ Nmin : int > 0 Min number of consecutive values below threshold. """ s = pd.Series(s) m = np.logical_and.reduce([s.shift(-i).le(thresh) for i in range(Nmin)]) if Nmin > 1: m = pd.Series(m, index=s.index).replace({False: np.NaN}).ffill(limit=Nmin-1).fillna(False) else: m = pd.Series(m, index=s.index)

# Form consecutive groups
gps = m.ne(m.shift(1)).cumsum().where(m)

# Return None if no groups, else the aggregations
if gps.isnull().all():
    return [0]
else:
    d = s.groupby(gps).agg([list, sum, 'size']).reset_index(drop=True)

    data = np.sum((d['size']))

    return data

```

 obj is 3d data of shape (324x180x360) (time,lat,lon)

``` python def consec_events(obj):

  time_nums = xr.DataArray(obj['time'].values.astype(np.float),
                         dims='time',
                         coords={'time': obj['time']},
                         name='time_nums')
   trend = xr.apply_ufunc(get_grps,time_nums, obj,
                       vectorize=True,
                       input_core_dims=[['time'], ['time']],
                       output_core_dims=[[]],
                       output_dtypes=[np.float],
                       dask='parallelized',output_sizes={'ntime':time_nums.shape[0]})

return trend

results = consec_events(spi) ```

ERROR IS HERE

... File "/Users/mada0007/anaconda3/envs/RESEARCH_QUESTION_TWO/lib/python3.7/site-packages/numpy/lib/function_base.py", line 2157, in _vectorize_call res = self._vectorize_call_with_signature(func, args) File "/Users/mada0007/anaconda3/envs/RESEARCH_QUESTION_TWO/lib/python3.7/site-packages/numpy/lib/function_base.py", line 2221, in _vectorize_call_with_signature output[index] = result ValueError: setting an array element with a sequence.

I am relatively new to apply this and I have been reading quite a lot. I would appreciatiate if I can be corrected on how to properly apply this over time dimension of my data and get resulting 2d array for each lon and lat?

There has been updated to IPCC srex regions which has not yet been implemented in xarray I think.

In particular I am looking for how I can subset this new cordinate for CENTRAL africa

AFRICA;Central-Africa;CAF; 8,-10.0; 8,0; 15.0,14.7; 27.0,14.7; 27.0,-10.0;;;;;;;;;

Values on the right are longitudes and values on the left are lattitudes respectively.

Code Sample, a copy-pastable example if possible

python dset = xr.open_mfdataset('/Users/mada0007/Desktop/Spi1_data/*.nc',autoclose=True) spi_all = dset['pr'][:,:,:] spi_lat = dset['lat'][:] spi_lon = dset['lon'][:]

this is my error message

```python-traceback Traceback (most recent call last): File "", line 1, in <module> File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/backends/api.py", line 637, in open_mfdataset datasets = [open_(p, **open_kwargs) for p in paths] File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/backends/api.py", line 344, in open_dataset ds = maybe_decode_store(store) File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/backends/api.py", line 274, in maybe_decode_store drop_variables=drop_variables) File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/conventions.py", line 461, in decode_cf decode_coords, drop_variables=drop_variables) File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/conventions.py", line 394, in decode_cf_variables stack_char_dim=stack_char_dim) File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/conventions.py", line 300, in decode_cf_variable var = coder.decode(var, name=name) File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/coding/times.py", line 412, in decode dtype = _decode_cf_datetime_dtype(data, units, calendar) File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/coding/times.py", line 131, in _decode_cf_datetime_dtype raise ValueError(msg) ValueError: unable to decode time units u'days since 0001-01-01' with calendar u'days since 0001-01-01'. Try opening your dataset with decode_times=False. Full traceback: Traceback (most recent call last): File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/coding/times.py", line 122, in _decode_cf_datetime_dtype result = decode_cf_datetime(example_value, units, calendar) File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/coding/times.py", line 192, in decode_cf_datetime flat_num_dates.astype(np.float), units, calendar) File "/Users/mada0007/anaconda3/envs/Research_ass/lib/python2.7/site-packages/xarray/coding/times.py", line 92, in _decode_datetime_with_cftime only_use_cftime_datetimes=True)) File "cftime/_cftime.pyx", line 265, in cftime._cftime.num2date File "cftime/_cftime.pyx", line 730, in cftime._cftime.utime.init

ValueError: calendar must be one of ['standard', 'gregorian', 'proleptic_gregorian', 'noleap', 'julian', 'all_leap', '365_day', '366_day', '360_day'], got 'days since 0001-01-01'

```

Problem description

trying to open this netcdf files which was writtend by me, code not working at all expecting ext

Output of xr.show_versions()

This is my code

```python R = OM.rolling(time=59) for label, arr_window in R: aa_try = dset.precip \ .where(dset.precip < 50) \ .count(dim='time')

```

so my data is of shape 324,72,144 i.e. time,lon and lat. I want to do a rolling count over the time dimention with threshold as specified above. the problem is I expect to get data of the same dimension but instead I get only 2d data. Is there anyway to get around this? Any advice will be very helpfull.

[this should explain why the current behavior is a problem and why the expected output is a better solution.]