cvanelteren

import strutils, strformat, os, random, times
import dynlib
import nimpy, nimpy/py_lib, nimpy/py_types
{.pragma: pyfunc, cdecl, gcsafe.}
import locks
import malebolgia, math
import random, os

import chronos

cvanelteren

import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import numpy as np

def create_continuous_colormap(colors, name='custom_colormap'):
    # Define color positions (evenly spaced between 0 and 1)
    n = len(colors)
    positions = np.linspace(0, 1, n)

    # Create a colormap

cvanelteren

#!/usr/bin/env bashgit clone --bare [email protected]:cvanelteren/dots.git $HOME/.dotfiles# define config alias locally since the dotfiles
# aren't installed on the system yet
function config {
   git --git-dir=$HOME/.dotfiles/ --work-tree=$HOME $@
}# create a directory to backup existing dotfiles to
mkdir -p .dotfiles-backup
config checkout
if [ $? = 0 ]; then
  echo "Checked out dotfiles from [email protected]:cvanelteren/dotfiles.git";
  else

cvanelteren

import matplotlib.pyplot as plt
from matplotlib.offsetbox import OffsetImage, AnnotationBbox

g = nx.krackhardt_kite_graph()
pos = nx.kamada_kawai_layout(g)

example = "unknown.jpg"

fig, ax = plt.subplots()
output_size = 25

cvanelteren

import proplot as plt, cmasher as cmr, pandas as pd,\
    numpy as np, os, sys, networkx as nx, warnings,\
    re
from pathlib import Path
warnings.simplefilter("ignore")


g = nx.krackhardt_kite_graph()
pos = nx.kamada_kawai_layout(g)

cvanelteren

import proplot as plt, networkx as nx, pandas as pd

def bundle(g: nx.Graph, pos: dict):
    from datashader.bundling import hammer_bundle
    edges = []
    for u, v in g.edges():
        row = dict(source=u, target=v)
        edges.append(row)
    edges = pd.DataFrame(edges)

cvanelteren

import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection



def fill_between_3d(ax,x1,y1,z1,x2,y2,z2,mode=1,c='steelblue',alpha=0.6):

    """

cvanelteren

def arc_layout(
    G: nx.Graph, subset_key="subset", radius=1, rotation=0, offset=0
) -> dict:
    """Arc layout for networkx

    Provides  a   layout  where  a  multipartite   graph  is
    displayed  on a  unit circle.  This could  provide clear
    visuals for data that is highly clustered.

    Parameters

cvanelteren

import proplot as plt, cmasher as cmr, pandas as pd, numpy as np, os, sys, networkx as nx, warnings


def multilayer_layout(
    G: nx.Graph,
    subset_key="layer",
    layout=nx.spring_layout,
    separation: float = 10.0,
) -> dict:
    # set positions

cvanelteren

{"directed": false, "multigraph": false, "graph": {"name": "Krackhardt Kite Social Network"}, "nodes": [{"id": 0}, {"id": 1}, {"id": 2}, {"id": 3}, {"id": 4}, {"id": 5}, {"id": 6}, {"id": 7}, {"id": 8}, {"id": 9}], "links": [{"source": 0, "target": 1}, {"source": 0, "target": 2}, {"source": 0, "target": 3}, {"source": 0, "target": 5}, {"source": 1, "target": 3}, {"source": 1, "target": 4}, {"source": 1, "target": 6}, {"source": 2, "target": 3}, {"source": 2, "target": 5}, {"source": 3, "target": 4}, {"source": 3, "target": 5}, {"source": 3, "target": 6}, {"source": 4, "target": 6}, {"source": 5, "target": 6}, {"source": 5, "target": 7}, {"source": 6, "target": 7}, {"source": 7, "target": 8}, {"source": 8, "target": 9}]}