def simple_optimazation_app():
population_cnt = 20
itter_time = 50
crossover_rate = 0.1
drop_rate = 0.5
mutation_rate = 0.1
i = 0
best_score = 0
best_ind = []
best_ind_ready = []
population = []
'''
dynamic figure
'''
X = np.linspace(0, 1, 1000)
y = np.array([target_function(x) for x in X])
x_sc = LinearScale()
y_sc = LinearScale()
ref = Lines(x=X, y=y, scales={'x': x_sc, 'y': y_sc})
# scatter = Scatter(x=[population], y=np.array([target_function(ind) for ind in population]),
# scales={'x': x_sc, 'y': y_sc},
# colors=['DarkOrange'], stroke='red',
# stroke_width=0.4, default_size=20)
scatter = Scatter(x=[],
y=[],
scales={
'x': x_sc,
'y': y_sc
},
colors=['DarkOrange'],
stroke='red',
stroke_width=0.4,
default_size=20)
x_ax = Axis(label='X', scale=x_sc)
y_ax = Axis(label='Y', scale=y_sc, orientation='vertical')
x_ax.min = 0
x_ax.max = 1
x_ax.num_ticks = 7
x_ax.grid_color = 'orangered'
fig = Figure(marks=[ref, scatter],
title='A Figure',
axes=[x_ax, y_ax],
animation_duration=1000)
# display(fig)
# %%
run_itter_slider = population_slider = widgets.IntSlider(
value=50, description='#Iteration', min=1, max=100, step=1)
run_btn = widgets.Button(description='Run', icon='play', disabled=True)
population_cnt_slider = widgets.IntSlider(value=30,
description='#Population',
min=0,
max=100,
step=10)
init_population_btn = widgets.Button(description='Initialize Population')
descriptor1 = widgets.Label('crossover_rate')
crossover_rate_slider = widgets.FloatSlider(value=0.1,
description='',
min=0,
max=1.0,
step=0.1)
descriptor2 = widgets.Label('drop_rate')
drop_rate_slider = widgets.FloatSlider(value=0.5,
description='',
min=0,
max=1.0,
step=0.1)
descriptor3 = widgets.Label('mutation_rate')
mutation_rate_slider = widgets.FloatSlider(value=0.3,
description='',
min=0,
max=1.0,
step=0.1)
patch1 = widgets.HBox([descriptor1, crossover_rate_slider])
patch2 = widgets.HBox([descriptor2, drop_rate_slider])
patch3 = widgets.HBox([descriptor3, mutation_rate_slider])
blank = widgets.Label('')
run_out = widgets.Output(layout={
'border': '1px solid black',
'height': '50px'
})
row1 = widgets.VBox([population_cnt_slider, init_population_btn])
row2 = widgets.HBox([patch1, patch2, patch3])
row_n = widgets.VBox([run_itter_slider, run_btn])
app = widgets.VBox([row1, blank, row2, blank, row_n, run_out, fig])
# %%
def initialize():
nonlocal population, i
population = np.random.rand(population_cnt_slider.value)
scatter.x = population
scatter.y = get_scores(scatter.x)
i = 0
fig.title = f'迭代{i}次\n'
@run_out.capture()
def update(itter_time=itter_time,
crossover_rate=crossover_rate,
drop_rate=drop_rate,
mutation_rate=mutation_rate):
nonlocal scatter, fig, best_score, best_ind_ready, best_ind, i
for j in range(itter_time):
new_population = select_and_crossover(
population, crossover_rate=crossover_rate, drop_rate=drop_rate)
new_population_ready = encode_all(new_population)
new_population_ready = mutatie_all(new_population_ready,
mutation_rate=mutation_rate)
new_population = decode_all(new_population_ready)
ind, score = get_best(new_population)
if score > best_score:
best_ind = ind
best_score = score
best_ind_ready = encode(best_ind)
i += 1
scatter.x = new_population
scatter.y = get_scores(new_population)
fig.title = f'迭代{i}次' # + f'最优个体为: {best_ind_ready}; 函数值为:{best_score}'
clear_output(wait=True)
display(f'最优个体为: {best_ind_ready}; 函数值为:{best_score}')
# %%
# update()
# %%
def on_click_init(change):
initialize()
run_btn.disabled = False
def on_click_run(change):
update(itter_time=run_itter_slider.value,
crossover_rate=crossover_rate_slider.value,
drop_rate=drop_rate_slider.value,
mutation_rate=mutation_rate_slider.value)
init_population_btn.on_click(on_click_init)
run_btn.on_click(on_click_run)
return app
x_sc = LinearScale()
y_sc = LinearScale()
ref = Lines(x=X, y=y, scales={'x': x_sc, 'y': y_sc})
scatter = Scatter(x=population, y=np.array([target_function(ind) for ind in population]),
scales={'x': x_sc, 'y': y_sc},
colors=['DarkOrange'], stroke='red',
stroke_width=0.4, default_size=20)
x_ax = Axis(label='X', scale=x_sc)
y_ax = Axis(label='Y', scale=y_sc, orientation='vertical')
x_ax.min = 0
x_ax.max = 1
x_ax.num_ticks = 7
x_ax.grid_color = 'orangered'
fig = Figure(marks=[ref, scatter], title='A Figure', axes=[x_ax, y_ax],
animation_duration=1000)
fig
# %%
scatter.x=np.random.rand(30)
scatter.y=np.array([target_function(ind) for ind in scatter.x])
# %%
from ipywidgets import widgets
math_expression = widgets.Label(r'\( f(x) = \exp(-(x-0.1)^2)\times\sin^2(6\pi x^{3/4}) \)')
# %%
