"""
.. _point_cell_scalars_example:

Point Cell Scalars
~~~~~~~~~~~~~~~~~~

This example demonstrates how to add point scalars for each individual cell to
a dataset.


"""

import numpy as np
from pyvista import examples

# %%
# load the first 4 cells from the example UnstructuredGrid. Note how the number
# of points is less than 32 since all the points are joined in the center.
grid = examples.load_hexbeam().extract_cells(range(4))
grid


# %%
# Plot Point Scalars
# ~~~~~~~~~~~~~~~~~~
# At this point it's possible to assign only point or cell scalars to this
# dataset. First, let's just plot some simple point scalars.

grid.point_data['Point Data'] = range(grid.n_points)
grid.plot(scalars='Point Data')


# %%
# Plot Cell Scalars
# ~~~~~~~~~~~~~~~~~
# Next, let's plot cell scalars. We're simply assigning based on the cell
# index.
grid.cell_data['Cell Data'] = range(grid.n_cells)
grid.plot(scalars='Cell Data')


# %%
# Splitting the Cells
# ~~~~~~~~~~~~~~~~~~~
# If you wanted to assign data to each point of each cell and plot that, it's
# simply not possible since these hexahedral cells all share the same
# points. To split up individual cells, separate them using
# :func:`pyvista.DataSetFilters.separate_cells`.
#
# With this filter the resulting :class:`pyvista.UnstructuredGrid` now contains
# 32 points, or 8 for each cell. They are now fully separated with no shared
# points.

split_cells = grid.separate_cells()
split_cells


# %%
# Plot Point Cell Data
# ~~~~~~~~~~~~~~~~~~~~
# Now we can plot values for each point for each cell. This will still be
# assigned to the point data.
#
# Here we use :func:`numpy.hstack` for clarity, but as long as the length of
# the data matches the number of points, you'll be able to use this approach.
#
# See how the plotted values appear continuous within a cell and discontinuous
# between cells. This matches how stresses and strains are calculated from
# finite element solutions.

split_cells.point_data['Point Cell Data'] = np.hstack(
    (
        np.linspace(0, 8, 8),  # cell 0
        np.linspace(0, 12, 8),  # cell 1
        np.linspace(0, 16, 8),  # cell 2
        np.linspace(0, 20, 8),  # cell 3
    ),
)
split_cells.plot(scalars='Point Cell Data')
# %%
# .. tags:: plot
