This PR resolves issue #682 and #572.

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PR Description

Please describe the changes proposed in the pull request:

Hi, first just want to express my gratitude for making this fantastic package!

In this PR, I've just simply added node_palette and edge_palette kwargs with the main idea to allow circos to accept either a list or dictionary of custom color palettes for colouring categories. annotate.node_colormapping and annotate.edge_colormapping also received a similar treatment but accepts palette as the kwarg.

This gets around the issue of only limited to 12 colours and allow for custom color selection. I've inserted the kwargs into the functions in .api but I've only tried this on circos so i'm not sure if it impacts on the rest of the package.

Minimal example to illustrate the outcome:

import networkx as nx
import nxviz as nv
import matplotlib.pyplot as plt
from itertools import cycle
from nxviz import annotate

# 14 categories
categories = [
    "sun",
    "moon",
    "stars",
    "cloud",
    "wheel",
    "box",
    "plant",
    "chair",
    "slippers",
    "tablet",
    "laptop",
    "dishwasher",
    "bicycle",
    "piano",
    "laptop",
]

# 20 colors - providing an uneven list on purpose
palette = [
    "#1f77b4",
    "#ff7f0e",
    "#279e68",
    "#d62728",
    "#aa40fc",
    "#8c564b",
    "#e377c2",
    "#b5bd61",
    "#17becf",
    "#aec7e8",
    "#ffbb78",
    "#98df8a",
    "#ff9896",
    "#c5b0d5",
    "#c49c94",
    "#f7b6d2",
    "#dbdb8d",
    "#9edae5",
    "#ad494a",
    "#8c6d31",
]

categorical = cycle(categories[0:4]) # max 4 distinct categories
categories[0:4]
# ['sun', 'moon', 'stars', 'cloud']
many_categorical = cycle(categories) # up to 14

n = 71
p = 0.01
G = nx.erdos_renyi_graph(n=n, p=p)

for n in G.nodes():
    G.nodes[n]["group1"] = next(categorical)
    G.nodes[n]["group2"] = next(many_categorical) # up to 14
for u, v in G.edges():
    G.edges[u, v]["edge_group1"] = next(categorical)
    G.edges[u, v]["edge_group2"] = next(many_categorical) # up to 14
    G.edges[u, v]["thickness"] = 3  # just to be able see the edge colours later

Current default behavior as it is right now (before/after this PR) i.e. don't specify the palette options:

nv.circos(G, group_by="group1", node_color_by="group1")
annotate.node_colormapping(G, color_by="group1")

when there's >12 categories, just modified the error message to ask for people to provide their own palette.

nv.circos(G, group_by="group2", node_color_by="group2")

this PR's proposed changes:

nv.circos(G, group_by="group1", node_color_by="group1", node_palette=palette[:4]) # specify 4 colors for 4 groups

now with more than 12 categories (14), and a long color palette (20 colors)

nv.circos(G, group_by="group2", node_color_by="group2", node_palette=palette)

same as above but limit to 7 colors - colors start to cycle if palette is provided as a list.

nv.circos(G, group_by="group2", node_color_by="group2", node_palette=palette[:7])

if provided as a dictionary:

pal = {'moon':'red', 'stars':'yellow', 'sun':'black', 'cloud':'blue'}
nv.circos(G, group_by="group1", node_color_by="group1", node_palette=pal)
annotate.node_colormapping(G, color_by="group1", palette=pal)

order of keys don't matter

pal = {'moon':'red', 'cloud':'pink', 'stars':'yellow', 'sun':'black'}
nv.circos(G, group_by="group1", node_color_by="group1", node_palette=pal)
annotate.node_colormapping(G, color_by="group1", palette=pal)

can mix colors/hex codes

pal = ['pink', '#1f77B4', 'green', '#ff7f0e']
nv.circos(G, group_by="group1", node_color_by="group1", node_palette=pal)
annotate.node_colormapping(G, color_by="group1", palette=pal)

swapping of order of colors in a list matters. But the plot should reflect this correctly - if you look up at the dictionary examples, the same order is preserved.

pal = ['pink', '#1f77B4', '#ff7f0e', 'green'] # swapped the order of the last two colours
nv.circos(G, group_by="group1", node_color_by="group1", node_palette=pal)
annotate.node_colormapping(G, color_by="group1", palette=pal)

Can be used on edges as well:

nv.circos(G, 
          group_by="group2", 
          node_color_by="group2", 
          edge_color_by = 'edge_group1', 
          node_palette=palette, 
          edge_palette = palette,
          edge_lw_by = 'thickness',
         )
annotate.node_colormapping(G, color_by="group2", palette=palette)
annotate.edge_colormapping(G, color_by="edge_group1", palette=palette)

As a sanity check, just to ensure that the color/order is respected you can see in this small graph where only 2 categories will be repeated twice (sun and moon), the color mapping remains consistent:

default i.e. palette not provided

n = 6
p = .01
G = nx.erdos_renyi_graph(n=n, p=p)
assignments = []
for n in G.nodes():
    G.nodes[n]["group1"] = next(categorical)
    assignments.append(G.nodes[n]["group1"])
    G.nodes[n]["group2"] = next(many_categorical)
assignments
# ['sun', 'moon', 'stars', 'cloud', 'sun', 'moon']
nv.circos(G, group_by="group1", node_color_by="group1")
annotate.node_colormapping(G, color_by="group1")

palette provided as a list. Because sun was added first (it was added sequentially as 'sun', 'moon', 'stars', 'cloud', 'sun', 'moon'), it should be pink. cloud is the last unique entry, so should be green.

pal = ['pink', '#1f77B4', '#ff7f0e', 'green']
nv.circos(G, group_by="group1", node_color_by="group1", node_palette=pal)
annotate.node_colormapping(G, color_by="group1", palette=pal)

palette is provided as a dictionary.

pal = {'moon':'red', 'stars':'yellow', 'sun':'black', 'cloud':'blue'}
nv.circos(G, group_by="group1", node_color_by="group1", node_palette=pal)
annotate.node_colormapping(G, color_by="group1", palette=pal)

let me know what you think!

Cheers, Kelvin

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@ericmjl

ericmjl / nxviz

Custom color mapping circos nodes and edges #689

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