<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def slice_along_axis(dataset, n=5, axis='x', tolerance=None, generate_triangles=False, contour=False):
 """Create many slices of the input dataset along a specified axis. Parameters n : int The number of slices to create axis : str or int The axis to generate the slices along. Perpendicular to the slices. Can be string name (``'x'``, ``'y'``, or ``'z'``) or axis index (``0``, ``1``, or ``2``). tolerance : float, optional The toleranceerance to the edge of the dataset bounds to create the slices generate_triangles: bool, optional If this is enabled (``False`` by default), the output will be triangles otherwise, the output will be the intersection polygons. contour : bool, optional If True, apply a ``contour`` filter after slicing """

        axes = {'x':0, 'y':1, 'z':2}
        output = vtki.MultiBlock()
        if isinstance(axis, int):
            ax = axis
            axis = list(axes.keys())[list(axes.values()).index(ax)]
        elif isinstance(axis, str):
            try:
                ax = axes[axis]
            except KeyError:
                raise RuntimeError('Axis ({}) not understood'.format(axis))
        # get the locations along that axis
        if tolerance is None:
            tolerance = (dataset.bounds[ax*2+1] - dataset.bounds[ax*2]) * 0.01
        rng = np.linspace(dataset.bounds[ax*2]+tolerance, dataset.bounds[ax*2+1]-tolerance, n)
        center = list(dataset.center)
        # Make each of the slices
        for i in range(n):
            center[ax] = rng[i]
            slc = DataSetFilters.slice(dataset, normal=axis, origin=center,
                    generate_triangles=generate_triangles, contour=contour)
            output[i, 'slice%.2d'%i] = slc
        return output