Dear Toolbox team,
can you please guide me on how to deal the NaNs, PosInf, NegInf in the dataset? I'm using "cdstoolbox.stats.trend" to calculate the trend. Here is the error message:
File "/usr/local/lib64/python3.6/site-packages/scipy/optimize/minpack.py", line 708, in curve_fit
ydata = np.asarray_chkfinite(ydata, float)
File "/usr/local/lib64/python3.6/site-packages/numpy/lib/function_base.py", line 496, in asarray_chkfinite
"array must not contain infs or NaNs")
ValueError: array must not contain infs or NaNs
There is an input argument skipnan=True, but I can't manage to make it work.
TypeError: trend() got an unexpected keyword argument 'skipna'
Here is the full code I use to retrieve the data, prepare the data, calculate the trend and plot it.
import cdstoolbox as ct
layout = ct.Layout(rows=1, debug=False, input_ncols=2, justify='flex-start' )
layout.add_widget(row=0, content='output-0', sm=9)
variables = {'surface_downwelling_shortwave_flux': 'SIS'}
@ct.application()
@ct.output.figure()
def application():
request=[
'satellite-surface-radiation-budget', {
'variable': 'surface_downwelling_shortwave_flux',
'product_family': 'clara',
'climate_data_record_type': 'thematic_climate_data_record',
'origin': 'eumetsat',
'sensor': 'avhrr',
'time_aggregation': 'monthly_mean',
'year': [str(year) for year in range(2005, 2011)],
'month': ['%02d'%(mnth) for mnth in range(1,13)]
}
]
data = ct.catalogue.retrieve(*request)
anom = ct.operator.sub(data, ct.cube.average(data, 'time'))
trend = ct.stats.trend(anom, dim='time')
trd = trend[1]
trd = ct.operator.mul(trd,3.156e8)
trd = ct.units.convert_units(trd, target_units="kg.s-4")
fig = ct.cdsplot.geomap(
trd,
projection=ct.cdsplot.crs.PlateCarree(),
)
return fig
Kind regards,
Alex Bobryshev
