Heatmap scale greater than 1 vs less than equal to 1 about python-ternary HOT 4 CLOSED

Approach-1: Update the source code as mentioned in #191 (comment) .
Approach-2: Calculate the heatmap data with scale 100 but set the tick labels with scale 1.

import random
import numpy as np
'''
Principle: Creating heatmap w.r.t scale=100 but label the ticks with scale=1.
'''

def generate_random_heatmap_data(scale=5):
    from ternary.helpers import simplex_iterator
    d = dict()
    for (i,j,k) in simplex_iterator(scale):
        d[(i,j,k)] = random.random()
    return d

scale = 100
d = generate_random_heatmap_data(scale)
dd = {tuple(np.array(x[0])/scale): x[1] for x in d.items()}
#------------------------------------------------------------------------------
figure, tax = ternary.figure(scale=scale)
figure.set_size_inches(10, 8)
tax.heatmap(d, style="h")
tax.boundary()
tax.clear_matplotlib_ticks()
tax.get_axes().axis('off')
tax.set_title(f"Heatmap Test: Hexagonal (original scale={tax.get_scale()})")

# ------------- Create tick labels with scale 1 --------------------------
TickLabels = list(np.linspace(0,1,11,dtype=float)) 
tax.ticks(ticks=TickLabels, multiple=10, tick_formats={'b':'%.1f','l':'%.1f','r':'%.1f'})

from python-ternary.

The existing ternary heatmap function isn't intended to work with scale = 1. It assumes that you'll define your own triangulation of the simplex and compute the desired value for each i, j, k combination, much like heatmapf does if you supply a function that can compute the values. In this case scale controls how many lattice points of the simplex to evaluate, much like the gridsize parameter in matplotlib's hexbin function (but hexbin is otherwise more of a histogram).

from python-ternary.

Is there some way that we can at least rescale the axes/axis ticks to go from 0 to 1 while also getting heatmapf to work?

from python-ternary.

Thanks for the tip on adjusting the ticks.

I also found another alternative: use plt.tripcolors with a rescaled version of the points (derived from simplex_iterator) on tax.ax (where tax has scale 1).

from python-ternary.