Failed building wheel for llvmlite

[Amarounek]

Hello,

I was trying to use Climate Indices on my meteorological dataset by Win Anaconda and Win Clear Python. I always have some issues.

For example on clear python ( I know about the closed issue and it seems that date format is in correct format in my nc file):
TypeError: expected str, bytes or os.PathLike object, not NoneType

or by testing by yours nclimgrid_lowres_prcp.nc if something is different in my and yours dataset:

process_climate_indices --index spi --periodicity monthly --netcdf_precip "./nclimgrid_lowres_prcp.nc" --var_name_precip prcp --output_file_base "./Agrometeorological indicators/" --scales 6 --calibration_start_year 1895 --calibration_end_year 2017 --multiprocessing all

Output:

File "c:\users\lukat\scoop\apps\python\current\lib\site-packages\climate_indices\indices.py", line 110:
def spi(
    <source elided>
    # or to (years, 366) for daily
    if periodicity is compute.Periodicity.monthly:
    ^

So I decided to use WSL Python after reading the issues here and since it seems as the most stable system.

sudo pip3 install climate-indices

I have an error with llvmlite:

Failed building wheel for llvmlite

I was trying to find a solution but unsuccessful. There are lots of tutorials however, no one really helps me...

[Amarounek]

Okay

Seems that Anaconda on Linux will be the most suitable solution. "Failed building wheel for llvmlite" - seems that this is only an issue of clear python and pip installation. The test run goes well with nclimgrid_lowres_prcp.nc

However with my cropped file, the issue is still same:
TypeError: expected str, bytes or os.PathLike object, not NoneType

I will try to find a solution with xarray or NetCDF4.

[Amarounek]

Okay! I got it!
You need to put in the right order dimensions!

<xarray.Dataset>
Dimensions:             (lat: 115, lon: 140, time: 15157)
Coordinates:
  * lat                 (lat) float64 -7.4 -7.5 -7.6 -7.7 ... -18.6 -18.7 -18.8
  * lon                 (lon) float64 21.1 21.2 21.3 21.4 ... 34.8 34.9 35.0
  * time                (time) datetime64[ns] 1979-01-01 ... 2020-06-30
Data variables:
    Precipitation_Flux  (time, lat, lon) float32 ...
Attributes:
    CDI:          Climate Data Interface version 1.9.2 (http://mpimet.mpg.de/...
    history:      Sat Nov 28 18:08:48 2020: ncks -v Precipitation_Flux -d lon...
    Conventions:  CF-1.7
    CDO:          Climate Data Operators version 1.9.2 (http://mpimet.mpg.de/...
    NCO:          netCDF Operators version 4.7.9 (Homepage = http://nco.sf.ne...

So this should work!

import xarray as xr
data = data.transpose("lat", "lon", "time")

[monocongo]

Sorry I couldn't help with this earlier, @Amarounek

What was the cause of the initial TypeError? I'm curious about that because I thought the dimensions being out of order should cause a separate error. But maybe something else was going on?

[Amarounek]

No problem!

Well If I run it on Windows Python distribution (all installed by pip, however I am not quite sure how NCO is solved):

process_climate_indices --index spi --periodicity monthly --netcdf_precip monthly_output2.nc --var_name_precip Precipitation_Flux --output_file_base ./ --scales 12 --calibration_start_year 1979 --calibration_end_year 2020 --multiprocessing all

I have this type of error:

Traceback (most recent call last):
  File "c:\users\lukat\scoop\apps\python\current\lib\runpy.py", line 197, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "c:\users\lukat\scoop\apps\python\current\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\lukat\scoop\apps\python\current\Scripts\process_climate_indices.exe\__main__.py", line 7, in <module>
  File "c:\users\lukat\scoop\apps\python\current\lib\site-packages\climate_indices\__main__.py", line 1684, in main
    _compute_write_index(kwrgs)
  File "c:\users\lukat\scoop\apps\python\current\lib\site-packages\climate_indices\__main__.py", line 1011, in _compute_write_index
    _parallel_process(keyword_arguments["index"],
  File "c:\users\lukat\scoop\apps\python\current\lib\site-packages\climate_indices\__main__.py", line 1298, in _parallel_process
    pool.map(_apply_along_axis, chunk_params)
  File "c:\users\lukat\scoop\apps\python\current\lib\multiprocessing\pool.py", line 364, in map
    return self._map_async(func, iterable, mapstar, chunksize).get()
  File "c:\users\lukat\scoop\apps\python\current\lib\multiprocessing\pool.py", line 771, in get
    raise self._value
numba.core.errors.UnsupportedError: Failed in object mode pipeline (step: analyzing bytecode)
Use of unsupported opcode (IS_OP) found

File "c:\users\lukat\scoop\apps\python\current\lib\site-packages\climate_indices\indices.py", line 110:
def spi(
    <source elided>
    # or to (years, 366) for daily
    if periodicity is compute.Periodicity.monthly:

So I installed the Anaconda on WSL and I was able to get over the Failed building wheel for llvmlite during the Python distribution installation on WSL.

Then my script was easy:

import netCDF4
from netCDF4 import Dataset
import xarray as xr

data = xr.open_dataset('C3S_concat_cropped.nc')
data = data.transpose("lat", "lon", "time")
monthly_dataset = data['Precipitation_Flux'].resample(time ='m', skipna=False).sum()
monthly_dataset.attrs['units'] = 'mm'
new_filename_1 = './monthly_output2.nc'
print ('saving to ', new_filename_1)
monthly_dataset.to_netcdf(path=new_filename_1)

Following Climate Indices run was successful!

I cannot tell you about the Climate Indices installation in Anaconda distribution on Windows since I was going after the easiest way.