glidertools.mapping.grid_data¶
-
glidertools.mapping.
grid_data
(x, y, var, bins=None, how='mean', interp_lim=6, verbose=True, return_xarray=True)¶ Grids the input variable to bins for depth/dens (y) and time/dive (x). The bins can be specified to be non-uniform to adapt to variable sampling intervals of the profile. It is useful to use the
gt.plot.bin_size
function to identify the sampling intervals. The bins are averaged (mean) by default but can also be themedian, std, count
,Parameters: - x (np.array, dtype=float, shape=[n, ]) – The horizontal values by which to bin need to be in a psudeo discrete
format already. Dive number or
time_average_per_dive
are the standard inputs for this variable. Hasp
unique values. - y (np.array, dtype=float, shape=[n, ]) – The vertical values that will be binned; typically depth, but can also be density or any other variable.
- bins (np.array, dtype=float; shape=[q, ], default=[0 : 1 : max_depth ]) – Define the bin edges for y with this function. If not defined, defaults to one meter bins.
- how (str, defualt='mean') – the string form of a function that can be applied to pandas.Groupby
objects. These include
mean, median, std, count
. - interp_lim (int, default=6) – sets the maximum extent to which NaNs will be filled.
Returns: glider_section – A 2D section in the format specified by
ax_xarray
input.Return type: xarray.DataArray, shape=[p, q]
Raises: Userwarning
– Triggers whenx
does not have discrete values.- x (np.array, dtype=float, shape=[n, ]) – The horizontal values by which to bin need to be in a psudeo discrete
format already. Dive number or