infer interval and create new x and y grid to plot data with pcolormesh without loosing the last row and column (code snipet from xarray/plot/utils)

infer_interval_breaks

def xr_infer_interval_breaks(coord, axis=0):
    """
    Code from xarray: (github/pydata/xarray/plot/utils)    
    Usage: if x is a 2d array of longitudes...
    x = _infer_interval_breaks(x, axis=1)
    x = _infer_interval_breaks(x, axis=0) # repeat for second axis
    """
    deltas = 0.5 * np.diff(coord, axis=axis)
    first = np.take(coord, [0], axis=axis) - np.take(deltas, [0], axis=axis)
    last = np.take(coord, [-1], axis=axis) + np.take(deltas, [-1], axis=axis)
    trim_last = tuple(slice(None, -1) if n==axis else slice(None) for n in range(coord.ndim))
    
    coord = np.concatenate([first, coord[trim_last]+deltas, last], axis=axis)
    
    return coord

def _infer_interval_breaks(coord):
    """
    Code from xarray: (github/pydata/xarray/plot/utils)
    
    If you want to plot with pcolormesh, it will chop off the last row/column becuase
    pcolormesh uses the box edges as the verticies, and not the center of the box.
    This function infers the gridpoints to position the points in the center of the box.
    
    This is slightly different from the xarray code, in that this one performs the
    infering on both axes before returning the final product.
    
    Usage: if x is a 2d array of longitudes...
    x = _infer_interval_breaks(x)
    """
    
    axis = 0
    deltas = 0.5 * np.diff(coord, axis=axis)
    first = np.take(coord, [0], axis=axis) - np.take(deltas, [0], axis=axis)
    last = np.take(coord, [-1], axis=axis) + np.take(deltas, [-1], axis=axis)
    trim_last = tuple(slice(None, -1) if n==axis else slice(None) for n in range(coord.ndim))
    
    coord = np.concatenate([first, coord[trim_last]+deltas, last], axis=axis)
    
    axis = 1
    deltas = 0.5 * np.diff(coord, axis=axis)
    first = np.take(coord, [0], axis=axis) - np.take(deltas, [0], axis=axis)
    last = np.take(coord, [-1], axis=axis) + np.take(deltas, [-1], axis=axis)
    trim_last = tuple(slice(None, -1) if n==axis else slice(None) for n in range(coord.ndim))
    
    coord = np.concatenate([first, coord[trim_last]+deltas, last], axis=axis)
    
    return coord