Added left,right,top_corner_label methods to allow labeling of ternary plot at each corner instead of along each axis. Folks in geology tend to draw plots this way. Future work might make the positioning of the labels within the canvas.

Im sorry for post this issue as it has been discussed before but things does not work the way i expected.

import pylab as p
import ternary as t

figure, d=t.figure(scale=1)

d.boundary(linewidth=2.0)
d.gridlines(multiple=0.1,color="blue",linewidth=0.8)

d.set_title(r"source flavour composition $\nu_e,\nu_\mu,\nu_\tau$",fontsize=20)
d.left_axis_label(r"$\nu_\tau$",fontsize=20,offset=0.12)
d.right_axis_label(r"$\nu_\mu$",fontsize=20)
d.bottom_axis_label(r"$\nu_e$",fontsize=20)
d._redraw_labels()

d.ticks(axis='brl',multiple=0.1)
p.axis('off')
point1=[(0.34669820676138435,0.3336302826666826,0.31967151057193305)]
d.scatter(point1, marker='D', color='green', label=r"$(\frac{1}{3},\frac{2}{3},0)$")
d.resize_drawing_canvas(scale=1.05)
d.legend()
d.show()

from the plot above, the point i plotted corresponds to the 3 value in point1, but if I were to read off from the plot the ticks labels are reversed. from @marcharper u suggested adding an argument to ticks, so i tried but it gave me error when i replace the ticks line to

d.ticks(axis='brl',multiple=0.1,ticks=[1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0])

TypeError: 'NoneType' object is not iterable

apologies again as this has been discuss before, but is annoying that the orientation of tick does not show the correct value I'm plotting.

edit: the value in point 1 correspond nu e,mu,tau respectively.

Re: issue #13 , determine how to allow users to specify the plotting coordinates and direction. Currently we have "012" for counterclockwise plotting of the three coordinates (as described in #13).

The current heatmap code places 001 at the lower left, while project_point places 100 at the lower left. My thought was that these conventions should match just in case you want to scatter and color polygons on the same MPL axis.

More generally, it might be nice if the user could specify which coordinate system to use when plotting. For an upright simplex, we can call the corners left, center, right. The user might designate which coordinate system to use by specifying one of: {'xyz', 'yzx', 'zxy', 'xzy', 'zyx', 'yxz'}. So for 'xyz', x = (1, 0, 0) is assigned to the left corner, y = (0, 1, 0) to the center, and z = (0, 0, 1) to the right corner. 'xyz' is probably going to the preferred one almost always.

I've found that 1.0.3 version converts all float ticks to integer which cause example examples/color_coded_heatmap.py to produce ticks 0,0,0,0,0,0,0,0,0,0,1 instead of 0.0,0.1,0.2,...1.0. This does not happen in version 1.0.1.

Hi @marcharper (and others),

I'm doing a ternary phase diagram, but I would like the colour to represent direction. So, I have x,y,z data for the three different ternary axes, but I also have x,y,z data for the colour map. I was hoping to plot the x,y,z as r,b,g and alpha (where alpha is transparency and would correspond to a magnitude). Any ideas on how I could do this?

Thanks, Fred

Dear Marc,

I am trying your example code colorbar_kwargs.py for my system. I am willing to plot my ternary phase diagram with calculated free energies. I have tried for some test case and realized that the free energy (i.e scatter points c values) are not really compatible with bar label. For instance, I have selected 3 points with 0, -5 and -9.5 values (in vmin=-10, vmax=0 range ). `# Scatter some points points = [(2,3,5),(2,1,7),(2,5,2)] c = [0, -5, -9.5]

cb_kwargs = {"shrink" : 0.6, "orientation" : "horizontal", "fraction" : 0.1, "pad" : 0.05, "aspect" : 30}

tax.scatter(points,marker='s',c=c,edgecolor='k',s=80,linewidths=0.5, vmin=-10, vmax=0, colorbar=True,colormap='jet',cbarlabel='Free Energy (eV)', cb_kwargs=cb_kwargs,zorder=3)`

Under that circumstances I suppose to have blue, green and red circles in the phase diagram, but this is not the case as seen in the image attached.

If you can give me a feedback, I will be appreciated. Thanks, Halil

Attached is crude plot of my understanding for how the heatmaps are calculated using triangular lattices. Essentially, each point is assigned to the lower-left corner of an upright triangle. The upside-down triangles are the averages of the upright triangles around them.

This makes sense and is probably the easiest thing to do, but the result can be a bit counter intuitive in that a grid at scale s was put on the simplex while a grid at scale s+1 is used for coloring. As an alternative, it might be nice to color each triangle to be the average of the points around it at the same scale (as shown in the bottom diagram). I might be able to tackle this in a week or so, but I thought I'd open an issue anyway.

Place your finger somewhere in the interior of the triangle. The way the ticks angle into the boundary of the triangle (the axes) suggests that the composition does not add up to 1.0... I think the ticks are oriented in incorrect angles. Am I right?

import ternary
scale = 10

figure, tax = ternary.figure(scale=scale)
tax.left_axis_label("Component 1", offset=0.15)
tax.right_axis_label("Component 0", offset=0.15)
tax.bottom_axis_label("Component 2", offset=-0.05)
tax.heatmapf(iast_loadings_component_0, boundary=False, 
             style="hexagonal", cmap=plt.cm.get_cmap("Blues"), vmax=10.0, vmin=0.0)
tax.boundary(linewidth=2.0)
tax.gridlines(color="blue", multiple=1) # Every 5th gridline, can be a float
# Set ticks
# tax.ticks(axis='lbr', color="black", linewidth=1)
tax.ticks(axis='lbr', color="black", linewidth=1, locations=np.arange(scale+1),
         ticks=["%.1f" % (1.0 * i / scale) for i in range(scale+1)], offset=0.03)
# Remove default Matplotlib Axes
# tax.line(p1, p2, linewidth=3., marker='s', color='green', linestyle=":")
tax._redraw_labels()
tax.set_title("Uptake, component 1", y=1.08)

tax.clear_matplotlib_ticks()
plt.tight_layout()
plt.savefig("Tertiary_diagram.png", format='png', dpi=300, facecolor=fig.get_facecolor())
tax.show()

I try implement the example of your README.md but I get this tracebak:

from matplotlib import pyplot
import ternary

## Boundary and Gridlines
scale = 40
figure, tax = ternary.figure(scale=scale)

# Draw Boundary and Gridlines
tax.boundary(color="black", linewidth=2.0)
tax.gridlines(color="blue", multiple=5) # Every 5th gridline, can be a float

# Set Axis labels and Title
fontsize = 20
tax.set_title("Simplex Boundary and Gridlines", fontsize=fontsize)
tax.left_axis_label("Left label $\\alpha^2$", fontsize=fontsize)
tax.right_axis_label("Right label $\\beta^2$", fontsize=fontsize)
tax.bottom_axis_label("Bottom label $\\Gamma - \\Omega$", fontsize=fontsize)

# Set ticks
ternary_ax.ticks(axis='lbr', color="black", linewidth=1)

# Remove default Matplotlib Axes
tax.clear_matplotlib_ticks()

pyplot.show()
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-9-081775008589> in <module>()
      4 ## Boundary and Gridlines
      5 scale = 40
----> 6 figure, tax = ternary.figure(scale=scale)
      7 
      8 # Draw Boundary and Gridlines

AttributeError: module 'ternary' has no attribute 'figure'

I want to share color-bar between several ternary graphs which have individual value-range. For example, value-range of graph A is (0, 67), value-range of graph B is (65, 202) I want the color-bar which fits both of graph A and graph B.

Now, I have two color-bars and set of (color and number) does not match between A and B

This PR includes functionality for truncating the simplex i.e. cutting off one or more corners of the triangle to save whitespace. This has been recently mentioned in #192 and as I've been working on this for some time locally, I thought I'd share this code. I have added an truncated_simplex_example.py to the examples folder which gives a basic tutorial. There are convenience functions for getting and setting the ticks and tick labels which remain after the truncation. Truncation works with or without having set custom axis data limits.

This works for scatter plots but has not been tested on any of the heatmap plots.

Hi,

First I wanted to say thank you for creating such a well documented and useful package. I am attempting to use the heatmap() function but my current output is just a blank plot and I'm having trouble understanding why. I tried creating a dictionary where I mapped points to random values instead of the actual data I'm attempting to plot to see if it was an issue with my data but that's not working either. I think I'm likely doing something silly (maybe in my data generation?) but am pretty stuck and would appreciate any insight. As a note I'm omitting the boundaries where a coordinate is 0 because the distribution I hope to eventually plot behaves weirdly there, but this is something I intend to address later. Here's the code snippet:

import pandas as pd import numpy as np import matplotlib.pyplot as plt import ternary import random

def gen_rand_data(f1_list_all=np.linspace(0,1,100)): data = {} for f1 in f1_list_all: if f1 != 0: f2_list=f1_list_all[np.where(f1_list_all< 1-f1)] f1_list=f1*np.ones(f2_list.shape[0])

        for f2 in f2_list:
            if f2 > 0:
                val=random.uniform(0, 1)
                data[(f1, f2)] = val
                color=ternary.colormapping.colormapper(val) #testing to see that function converts to colors.
                print(color)
#print(data)
return data

def main(): f1_list_all=np.linspace(0,1,100) #data, Z=gen_data(f1_list_all) data = gen_rand_data(f1_list_all=np.linspace(0,1,100))

scale = 1

fig, ax = plt.subplots()
ax.axis("off")
figure, tax = ternary.figure(ax=ax, scale=scale)

tax.heatmap(data, cmap=None)

axes_colors = {'b': 'g', 'l': 'r', 'r': 'b'}
tax.boundary(linewidth=2.0)

tax.left_axis_label("$f_1$", offset=0.16)
tax.right_axis_label("$f_2$", offset=0.16)
tax.bottom_axis_label("$f_3$", offset=0.06)

tax.gridlines(multiple=1, linewidth=2,
          horizontal_kwargs={'color': axes_colors['b']},
          left_kwargs={'color': axes_colors['l']},
          right_kwargs={'color': axes_colors['r']},
          alpha=0.7)

# Set and format axes ticks.
ticks = [i / float(scale) for i in range(scale+1)]
tax.ticks(ticks=ticks, axis='rlb', linewidth=1, clockwise=True,
      axes_colors=axes_colors, offset=0.03, tick_formats="%0.1f")

tax.clear_matplotlib_ticks()
tax._redraw_labels()
plt.tight_layout()
tax.show()
figure.savefig('simplex_plot.png')

Thank you!

Description

The TernaryAxesSubplot.scatter() method skips the first color of the default matplotlib colormap in version 1.0.8.

Steps to reproduce

import ternary

fig, tax = ternary.figure(scale=1)
tax.scatter([(1.1/3, 0.9/3, 1/3)], label="first")
tax.scatter([(0.9/3, 1.1/3, 1/3)], label="second")
tax.legend()
tax.set_title(f"python-ternary {ternary.__version__}")
tax.show()

Expect behavior

The default matplotlib colors are used starting with blue, followed by orange, etc. This is the behavior with version 1.0.7:

Actual behavior

The first scatter plot uses the second default matplotlib color (orange), followed by the third (green), etc.:

Notes

Matplotlib version used in both cases above: 3.5.2

Hello!

First, thank you so much for making this package - it's so helpful! I am a geologist, and we often use ternary diagrams with the top cut off, such as the plot below (purely an example I got from the internet).

I am struggling to replicate this with your packages. I am using subplots, so I can control the height of the axes using ax.set_ylim, but this just stretches the ternary (example below), and leaves some of the ternary tick marks stretched out above the plot. Is there a way to plot only part of a ternary axis?

Basically, I guess I want to do something like the last part of the solution to #190 but without the free floating ticks.

Thank you! M

Added an option to all the relevant heatmap functions adj_vlims which will automatically scale the min and max values of the colormap used in the heatmap based on the min and max averaged values that are actually plotted on the heatmap.