"""
.. _scalar_bar_example:

Customize Scalar Bars
~~~~~~~~~~~~~~~~~~~~~

Walk through of all the different capabilities of scalar bars and
how a user can customize scalar bars.

"""

# sphinx_gallery_thumbnail_number = 2
import pyvista as pv
from pyvista import examples

# sphinx_gallery_start_ignore
# setting scalar bar position does not work in interactive plots
PYVISTA_GALLERY_FORCE_STATIC_IN_DOCUMENT = True
# sphinx_gallery_end_ignore

# %%
# By default, when plotting a dataset with a scalar array, a scalar bar for that
# array is added. To turn off this behavior, a user could specify
# ``show_scalar_bar=False`` when calling :func:`~pyvista.Plotter.add_mesh`.
# Let's start with a sample dataset provide via PyVista to demonstrate the default
# behavior of scalar bar plotting:

# Load St Helens DEM and warp the topography
mesh = examples.download_st_helens().warp_by_scalar()

# First a default plot with jet colormap
pl = pv.Plotter()
# Add the data, use active scalar for coloring, and show the scalar bar
pl.add_mesh(mesh)
# Display the scene
pl.show()

# %%
# We could also plot the scene with an interactive scalar bar to move around
# and place where we like by specifying passing keyword arguments to control
# the scalar bar via the ``scalar_bar_args`` parameter in
# :func:`pyvista.Plotter.add_mesh`. The keyword arguments to control the
# scalar bar are defined in :func:`pyvista.Plotter.add_scalar_bar`.

# create dictionary of parameters to control scalar bar
sargs = dict(interactive=True)  # Simply make the bar interactive

pl = pv.Plotter(notebook=False)  # If in IPython, be sure to show the scene
pl.add_mesh(mesh, scalar_bar_args=sargs)
pl.show()
# Remove from plotters so output is not produced in docs
pv.plotting.plotter._ALL_PLOTTERS.clear()


# %%
# .. figure:: ../../images/gifs/scalar-bar-interactive.gif
#
# Or manually define the scalar bar's location:

# Set a custom position and size
sargs = dict(height=0.25, vertical=True, position_x=0.05, position_y=0.05)

pl = pv.Plotter()
pl.add_mesh(mesh, scalar_bar_args=sargs)
pl.show()

# %%
# The text properties of the scalar bar can also be controlled:

# Controlling the text properties
sargs = dict(
    title_font_size=20,
    label_font_size=16,
    shadow=True,
    n_labels=3,
    italic=True,
    fmt='{0:.1f}',
    font_family='arial',
)

pl = pv.Plotter()
pl.add_mesh(mesh, scalar_bar_args=sargs)
pl.show()


# %%
# Labelling values outside of the scalar range
pl = pv.Plotter()
pl.add_mesh(
    mesh, clim=[1000, 2000], below_color='blue', above_color='red', scalar_bar_args=sargs
)
pl.show()


# %%
# Annotate values of interest using a dictionary. The key of the dictionary
# must be the value to annotate, and the value must be the string label.

# Make a dictionary for the annotations
annotations = {
    2300: 'High',
    805.3: 'Cutoff value',
}

pl = pv.Plotter()
pl.add_mesh(mesh, scalars='Elevation', annotations=annotations)
pl.show()
# %%
# .. tags:: plot
