def test_transform(self):
for tfm, itfm in [
(alr, inverse_alr),
(ilr, inverse_ilr),
(ILRTransform, None),
(ALRTransform, None),
]:
with self.subTest(tfm=tfm, itfm=itfm):
out = ternary_heatmap(self.data, transform=tfm, inverse_transform=itfm)
coords, H, data = out
df = pd.DataFrame(np.array([*get_scatter_points(n=80)]).T,
columns=["A", "B", "C"])
df = df.loc[(df > 0.1).all(axis=1), :]
#######################################################################################
# From this dataset we'll generate a
# :func:`~pyrolite.plot.density.ternary.ternary_heatmap`, which is the basis
# for ternary density diagrams via :func:`~pyrolite.plot.pyrochem.density`:
#
from pyrolite.comp.codata import ILR, inverse_ILR
from pyrolite.plot.density.ternary import ternary_heatmap
coords, H, data = ternary_heatmap(
df.values,
bins=10,
mode="density",
remove_background=True,
transform=ILR,
inverse_transform=inverse_ILR,
grid_border_frac=0.2,
)
#######################################################################################
# This function returns more than just the coordinates and histogram/density estimate,
# which will come in handy for exploring how it came together. The data variable here
# is a dictonary with contains the grids and coordiantes used to construct the
# histogram/density diagram. We can use these to show how the ternary log-grid is
# constructed, and then transformed back to ternary space before being triangulated
# and interpoalted for the ternary heatmap:
#
import matplotlib.pyplot as plt
import pyrolite.plot
from pyrolite.util.math import flattengrid
def test_need_inverse_transform(self):
for tfm, itfm in [(alr, None), (ilr, None)]:
with self.subTest(tfm=tfm, itfm=itfm):
out = ternary_heatmap(self.data,
transform=tfm,
inverse_transform=itfm)
def test_density(self):
out = ternary_heatmap(self.data, mode="density")
coords, H, data = out
self.assertTrue(coords[0].shape == coords[1].shape)
def test_histogram(self):
out = ternary_heatmap(self.data, mode="histogram")
xe, ye, zi = out
coords, H, data = out
self.assertTrue(coords[0].shape == coords[1].shape)
def test_default(self):
out = ternary_heatmap(self.data)
self.assertTrue(isinstance(out, tuple))
coords, H, data = out
self.assertTrue(coords[0].shape == coords[1].shape)
