"""
.. _connectivity_example:

Connectivity
~~~~~~~~~~~~

Use the connectivity filter to remove noisy isosurfaces.

This example is very similar to `this VTK example <https://kitware.github.io/vtk-examples/site/Python/VisualizationAlgorithms/PineRootConnectivity/>`__
"""
# sphinx_gallery_thumbnail_number = 2
import pyvista as pv
from pyvista import examples

###############################################################################
# Load a dataset that has noisy isosurfaces
mesh = examples.download_pine_roots()

cpos = [(40.6018, -280.533, 47.0172), (40.6018, 37.2813, 50.1953), (0.0, 0.0, 1.0)]

# Plot the raw data
p = pv.Plotter()
p.add_mesh(mesh, color='#965434')
p.add_mesh(mesh.outline())
p.show(cpos=cpos)

###############################################################################
# The mesh plotted above is very noisy. We can extract the largest connected
# isosurface in that mesh using the :func:`pyvista.DataSetFilters.connectivity`
# filter and passing ``largest=True`` to the ``connectivity``
# filter or by using the :func:`pyvista.DataSetFilters.extract_largest` filter
# (both are equivalent).

# Grab the largest connected volume present
largest = mesh.connectivity(largest=True)
# or: largest = mesh.extract_largest()

p = pv.Plotter()
p.add_mesh(largest, color='#965434')
p.add_mesh(mesh.outline())
p.camera_position = cpos
p.show()