xarray.Dataset.argo.groupby_pressure_bins
xarray.Dataset.argo.groupby_pressure_bins¶
- Dataset.argo.groupby_pressure_bins(bins: list, axis: str = 'PRES', right: bool = False, select: str = 'deep', squeeze: bool = True, merge: bool = True)¶
Group measurements by pressure bins
This method can be used to subsample and align an irregular dataset (pressure not being similar in all profiles) on a set of pressure bins. The output dataset could then be used to perform statistics along the
N_PROF
dimension becauseN_LEVELS
will corresponds to similar pressure bins, while avoiding to interpolate data.- Parameters
bins (list or np.array,) – Array of bins. It has to be 1-dimensional and monotonic. Bins of data are localised using values from options axis (default:
PRES
) and right (default:False
), see below.axis (str, default:
PRES
) – The dataset variable to use as pressure axis. This could bePRES
orPRES_ADJUSTED
right (bool, default: False) – Indicating whether the bin intervals include the right or the left bin edge. Default behavior is (right==False) indicating that the interval does not include the right edge. The left bin end is open in this case, i.e., bins[i-1] <= x < bins[i] is the default behavior for monotonically increasing bins. Note the
merge
option is intended to work only for the defaultright=False
.select ({'deep','shallow','middle','random','min','max','mean','median'}, default: 'deep') –
The value selection method for bins.
This selection can be based on values at the pressure axis level with:
deep
(default),shallow
,middle
,random
. For instance,select='deep'
will lead to the value returned for a bin to be taken at the deepest pressure level in the bin.Or this selection can be based on statistics of measurements in a bin. Stats available are:
min
,max
,mean
,median
. For instanceselect='mean'
will lead to the value returned for a bin to be the mean of all measurements in the bin.squeeze (bool, default: True) – Squeeze from the output bin levels without measurements.
merge (bool, default: True) – Optimize the output bins axis size by merging levels with/without data. The pressure bins axis is modified accordingly. This means that the return
STD_PRES_BINS
axis has not necessarily the same size as the inputbins
.
- Return type
See also
numpy.digitize
,argopy.utilities.groupby_remap