"""
.. _create_uniform_grid_example:

Creating a Uniform Grid
~~~~~~~~~~~~~~~~~~~~~~~

Create a simple uniform grid from a 3D NumPy array of values.
This example uses :class:`pyvista.ImageData`.

"""

import numpy as np
import pyvista as pv

# %%
# Take a 3D NumPy array of data values that holds some spatial data where each
# axis corresponds to the XYZ cartesian axes. This example will create a
# :class:`pyvista.ImageData` object that will hold the spatial reference for
# a 3D grid which a 3D NumPy array of values can be plotted against.

# %%
# Create the 3D NumPy array of spatially referenced data.
# This is spatially referenced such that the grid is 20 by 5 by 10
# (nx by ny by nz)
values = np.linspace(0, 10, 1000).reshape((20, 5, 10))
values.shape

# Create the spatial reference
grid = pv.ImageData()

# Set the grid dimensions: shape + 1 because we want to inject our values on
#   the CELL data
grid.dimensions = np.array(values.shape) + 1

# Edit the spatial reference
grid.origin = (100, 33, 55.6)  # The bottom left corner of the data set
grid.spacing = (1, 5, 2)  # These are the cell sizes along each axis

# Add the data values to the cell data
grid.cell_data['values'] = values.flatten(order='F')  # Flatten the array

# Now plot the grid
grid.plot(show_edges=True)


# %%
# Don't like cell data? You could also add the NumPy array to the point data of
# a :class:`pyvista.ImageData`. Take note of the subtle difference when
# setting the grid dimensions upon initialization.

# Create the 3D NumPy array of spatially referenced data
# This is spatially referenced such that the grid is 20 by 5 by 10
#   (nx by ny by nz)
values = np.linspace(0, 10, 1000).reshape((20, 5, 10))
values.shape

# Create the spatial reference
grid = pv.ImageData()

# Set the grid dimensions: shape because we want to inject our values on the
#   POINT data
grid.dimensions = values.shape

# Edit the spatial reference
grid.origin = (100, 33, 55.6)  # The bottom left corner of the data set
grid.spacing = (1, 5, 2)  # These are the cell sizes along each axis

# Add the data values to the cell data
grid.point_data['values'] = values.flatten(order='F')  # Flatten the array

# Now plot the grid
grid.plot(show_edges=True)
# %%
# .. tags:: load
