Odysseus#
This
1 Thing
will sort out everything: Iron Throne, Night King, Bending Knee
1. f(t)
\
2. S(t) -> 4. y:h'(t)=0; t(X'X).X'Y -> 5. b -> 6. SV'
/
3. h(t)
Wild 1, 2, 3#
Hideth: A prudent man foreseeth the evil, and hideth himself; but the simple pass on, and are punished. This is the seat of the
hunter-gatherer
who respondeth only to their senses of hungerSeeketh: The fearless will look out for fresh new dancing grounds at any opportunity, with attendant risks. This is the seat of the
peasant
who has decided to overcome the chaotic life of his forebearsFindeth: Longevity is never the goal: rather here & now, instantaneous: grief, love, humor, animus. This is the seat of the
farmer
who has mastered time, understands seasonality, and has tools that encode what his forebears did, thus allowing some surplus of produce. Energy source: chlorophyll
Tame 4#
Whineth: If ever under the wild & chaotinc natural elements; hence, catalog all good & evil; harness good. This is the seat of
manufacturing
in the history of civilization. A latent-space representing the distillation of all forebears and with innovative uses of the excessive produce for beer, wine, cheese, butter, wool, cotton, tobacco, and all the accoutrements we’ve become fond of. Energy source: hydrocarbons
Divine 5, 6#
Commandeth: leadership, decisiveness, hierarchy of priorities based on vector of coefficients. This is the seat of
energy
, which is always limited and has to be harnessed and directed at affordable costs to priority industries. The biological sources the hunter-gather, peasant, and farmer relied on efficiently harnessed energy via chlorophyll. But now in the social space man has to design energy-harnessing batteries and grids for non-biological products and servicesPersonalized needs catered to & this kind will bend the knee to King, Queen, AAA-MM-N. This is the seat of
deployment
. Unlike our forebear hunter-gatherer, peasant, and farmer who lived in proximity of their produce, our accoutrouments are not highly personalized, specialized, and produced to scale with ingredients and components from disparate geographic territories. The final product and service, then, has to be shipped, transported, or deployed into the hands of the end-user [1] [2] [3] [4] [5]. Energy source: nuclear [6][7][8]
Show code cell source
import os # Add this import statement
import networkx as nx
import matplotlib.pyplot as plt
import warnings
G = nx.DiGraph()
G.add_node("1. Root", pos=(-2500, 700))
G.add_node("2. Pentatonic", pos=(-4200, 0))
G.add_node("3. Diatonic", pos=(-2500, -700))
G.add_node("4. Chromatic", pos=(-1000, 0))
G.add_node("5. Temperament", pos=(1500, 0))
G.add_node("6. Expression", pos=(4000, 0))
G.add_edges_from([("1. Root", "4. Chromatic")])
G.add_edges_from([("2. Pentatonic", "4. Chromatic")])
G.add_edges_from([("3. Diatonic", "4. Chromatic")])
G.add_edges_from([("4. Chromatic", "5. Temperament")])
G.add_edges_from([("5. Temperament", "6. Expression")])
pos = nx.get_node_attributes(G, 'pos')
labels = {"4. Chromatic": "4. Dionysian",
"1. Root": "1. Chaos",
"2. Pentatonic": "2. Frenzy",
"3. Diatonic": "3. Emotion",
"5. Temperament": "5. Algorithm",
"6. Expression": "6. Binary"}
# Update color for the "Scenarios" node
node_colors = ["lightblue", "lightblue", "lightblue", "lavender", "lightblue", "lightblue"]
# Suppress the deprecation warning
warnings.filterwarnings("ignore", category=DeprecationWarning)
plt.figure(figsize=(10, 8))
nx.draw(G, pos, with_labels=False, node_size=20000, node_color=node_colors, linewidths=2, edge_color='black', style='solid')
nx.draw_networkx_labels(G, pos, labels, font_size=15)
nx.draw_networkx_edges(G, pos, edge_color='black', style='solid', width=2)
plt.xlim(-5000, 5000)
plt.ylim(-1000, 1000)
plt.axis("off")
# Specify the directory where the file should be saved
output_dir = os.path.expanduser("~/documents/liveserver/new") # Expand the user directory
if not os.path.exists(output_dir):
os.makedirs(output_dir)
# Save the plot as a PNG file in the specified directory
plt.savefig(os.path.join(output_dir, "self-criticism.png"))
plt.show()