def plot(m_bounds, h_bounds):
m_min, m_max = m_bounds
h_min, h_max = h_bounds
max_hits = np.array(range(m_min, m_max+1))
healths = np.array(range(h_min, h_max+1))
Ms, Hs = np.meshgrid(max_hits, healths)
fig, ax = config.get_figure(50, 18, scale=5 if showing else 10)
plt.xlabel("$h_0$", fontsize=25, labelpad=20)
plt.ylabel("$M$", fontsize=25, labelpad=20)
ax.set_zlabel("Turns to kill", fontsize=25, rotation=90, labelpad=20)
ax.tick_params(axis='z', labelsize=18)
ax.tick_params(axis='y', labelsize=18)
ax.tick_params(axis='x', labelsize=18)
A = np.vectorize(lambda m, h: MarkovChain().turns_to_kill(m, h))(Hs, Ms)
surf = ax.plot_surface(Hs, Ms, A, cmap=cm.hot)
A = np.vectorize(lambda m, h: Crude().turns_to_kill(m, h))(Hs, Ms)
surf = ax.plot_surface(Hs, Ms, A, cmap=cm.cool)
return plt
import osrsmath.combat.damage as damage
from matplotlib import cm
import matplotlib.pyplot as plt
import osrsmath.config as config
import numpy as np
import sys
import os
if __name__ == '__main__':
showing = len(sys.argv) >= 2 and sys.argv[1] == 'show'
fig, ax = config.get_figure(-124, 23, scale=5 if showing else 10)
plt.xlabel("$M$", fontsize=15)
plt.ylabel("$h$", fontsize=15)
ax.set_zlabel("Average Damage", fontsize=15, rotation=90)
h, M = 100, 100
y, x = np.meshgrid(range(h), range(M))
z = np.vectorize(damage.average)(y, x)
surf = ax.plot_surface(x, y, z, cmap=cm.coolwarm)
xs = range(min(h, M))
ax.plot(xs,
xs, [damage.average(x, x) for x in xs],
linewidth=2,
c='black',
zorder=3)
if showing:
plt.show()
else:
file_name = "average_damage"
[err(inverse(h, m), sim[str(h)][str(m)]) for m in max_hits])
for h in healths
])
surf = ax.plot_wireframe(Ms,
Hs,
Z,
color=colors[label],
linewidth=1,
label=f"{label}")
return {label: (np.average(Z), np.std(Z), np.max(Z), np.min(Z))}
for method in Model.__subclasses__():
if method.__name__ == 'Simulation':
continue
fig, ax = config.get_figure(33, 36, scale=3 if showing else 10)
plot_error(method.__name__, lambda h, m: method().turns_to_kill(h, m))
ax.tick_params(axis='z', labelsize=12)
ax.tick_params(axis='y', labelsize=12)
ax.tick_params(axis='x', labelsize=12)
ax.set_zlabel("Percent Error", fontsize=16, labelpad=20)
plt.xlabel("Max Hit", fontsize=16, labelpad=20)
plt.ylabel("Initial Health", fontsize=16, labelpad=20)
if showing:
plt.show()
else:
from pathlib import Path
file_name = str(Path(__file__).parent / method.__name__)
plt.savefig(f"{file_name}.png")
from matplotlib import cm
import matplotlib.pyplot as plt
import osrsmath.config as config
import numpy as np
import sys
import os
if __name__ == '__main__':
showing = len(sys.argv) >= 2 and sys.argv[1] == 'show'
a = range(1000)
d = range(1000)
a, d = np.meshgrid(a, d)
A = np.vectorize(accuracy)(a, d)
fig, ax = config.get_figure(-168, 25, scale=5 if showing else 10)
plt.xlabel("$A_{max}$", fontsize=15)
plt.ylabel("$D_{max}$", fontsize=15)
ax.set_zlabel("Accuracy", fontsize=15, rotation=90)
surf = ax.plot_surface(a, d, A, cmap=cm.coolwarm)
ax.plot([1000], [1000], [1.01])
ax.plot(range(1000),
range(1000), [accuracy(x, x) for x in range(1000)],
linewidth=2,
c='black',
zorder=3)
if showing:
plt.show()
else:
from osrsmath.results.part_II.colors import colors
from osrsmath.combat.successful_hits import *
from osrsmath.results.part_II.generate_simulation import load_dataset
from pprint import pprint
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import sys
import os
import osrsmath.config as config
if __name__ == '__main__':
showing = len(sys.argv) >= 2 and sys.argv[1] == 'show'
fig, ax = config.get_figure(38, 17, scale=3 if showing else 10)
m_min, m_max = (1, 110)
h_min, h_max = (1, 255)
max_hits = np.array(range(m_min, m_max+1))
healths = np.array(range(h_min, h_max+1))
Ms, Hs = np.meshgrid(max_hits, healths)
sim = load_dataset(N=100_000)
def plot_error(label, inverse):
""" inverse: hinv(h, m) """
def err(a, b):
# return abs(a - b)
return abs(1 - a /b)*100
print(label)
Z = np.array([np.array([err(inverse(h, m), sim[str(h)][str(m)]) for m in max_hits]) for h in healths])
surf = ax.plot_wireframe(Ms, Hs, Z, color=colors[label], linewidth=2.3, label=f"{label}")
return {label: (np.average(Z), np.std(Z), np.max(Z), np.min(Z))}