刪除 python 中繪制的 function

Question

問題是只要我在slider上設置一個新的function，舊的功能並沒有被刪除，但仍然顯示。 我試圖用clf和cla刪除之前的function，但是坐標系不再顯示（這里是clf和cla https的網站鏈接：//www.activestate.com/resources/quick-reads/how -to-clear-a-plot-in-python/ ）。 謝謝你的回答

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button, RadioButtons

# Select length of axes and the space between tick labels
xmin, xmax, ymin, ymax = -5, 5, -5, 5
ticks_frequency = 1

# Plot points
fig, ax = plt.subplots(figsize=(10, 10))

#////////////////////////////////////////////////////////////////////////////// 

# x range
x = np.arange(-5, 5., 0.025)

# start value
m1 = 1
t1 = 0
m2 = 1
t2 = 0

# Define the sliders position
ax_m1 = plt.axes([0.2, 0.075, 0.25, 0.03],)
ax_t1 = plt.axes([0.2, 0.125, 0.25, 0.03],)

ax_m2 = plt.axes([0.55, 0.075, 0.25, 0.03],)
ax_t2 = plt.axes([0.55, 0.125, 0.25, 0.03],)

# Define Slider value
mSlider1 = Slider(ax_m1, 'm1', -5.0, 5.0, valinit=m1, valstep=.01)
tSlider1 = Slider(ax_t1, 't1', -5.0, 5.0, valinit=t1, valstep=.01)

mSlider2 = Slider(ax_m2, 'm2', -5.0, 5.0, valinit=m2, valstep=.01)
tSlider2 = Slider(ax_t2, 't2', -5.0, 5.0, valinit=t2, valstep=.01)



#//////////////////////////////////////////////////////////////////////////////update

def update_m1(mSlider1):
    global m1
    m1 = mSlider1
    
def update_t1(tSlider1):
    global t1
    t1 = tSlider1
    
def update_m2(mSlider2):
    global m2
    m2 = mSlider2
    
def update_t2(tSlider2):
    global t2
    t2 = tSlider2

def update_f1(y1):
    y1 = m1*x + t1
    ax.plot(x, y1, lw = 3, alpha = 0.5, color="blue")

def update_f2(y2):
    y2 = m2*x + t2
    ax.plot(x, y2, lw = 3, alpha = 1, color = "orange")


mSlider1.on_changed(update_m1,)
tSlider1.on_changed(update_t1,)

mSlider1.on_changed(update_f1,)
tSlider1.on_changed(update_f1,)

mSlider2.on_changed(update_m2,)
tSlider2.on_changed(update_t2,)

mSlider2.on_changed(update_f2,)
tSlider2.on_changed(update_f2,)

#//////////////////////////////////////////////////////////////////////////////

# Set identical scales for both axes
ax.set(xlim=(xmin-1, xmax+1), ylim=(ymin-1, ymax+1), aspect='equal')

# Set bottom and left spines as x and y axes of coordinate system
ax.spines['bottom'].set_position('zero')
ax.spines['left'].set_position('zero')

# Remove top and right spines
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)

# Create 'x' and 'y' labels placed at the end of the axes
ax.set_xlabel('x', size=14, labelpad=-24, x=1.03)
ax.set_ylabel('y', size=14, labelpad=-21, y=1.02, rotation=0)

# Create custom major ticks to determine position of tick labels
x_ticks = np.arange(xmin, xmax+1, ticks_frequency)
y_ticks = np.arange(ymin, ymax+1, ticks_frequency)
ax.set_xticks(x_ticks[x_ticks != 0])
ax.set_yticks(y_ticks[y_ticks != 0])

# Create minor ticks placed at each integer to enable drawing of minor grid
# lines: note that this has no effect in this example with ticks_frequency=1
ax.set_xticks(np.arange(xmin, xmax+1), minor=True)
ax.set_yticks(np.arange(ymin, ymax+1), minor=True)

# Draw major and minor grid lines
ax.grid(which='both', color='grey', linewidth=1, linestyle='-', alpha=0.2)

# Draw arrows
arrow_fmt = dict(markersize=4, color='black', clip_on=False)
ax.plot((1), (0), marker='>', transform=ax.get_yaxis_transform(), **arrow_fmt)
ax.plot((0), (1), marker='^', transform=ax.get_xaxis_transform(), **arrow_fmt)

plt.show()

Answer 1

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button, RadioButtons

# Select length of axes and the space between tick labels
xmin, xmax, ymin, ymax = -5, 5, -5, 5
ticks_frequency = 1

# Plot points
fig, ax = plt.subplots(figsize=(10, 10))

#////////////////////////////////////////////////////////////////////////////// 

# x range
x = np.arange(-5, 5., 0.025)

# start value
m1 = 1
t1 = 0
m2 = 1
t2 = 0

# Define the sliders position
ax_m1 = plt.axes([0.2, 0.075, 0.25, 0.03],)
ax_t1 = plt.axes([0.2, 0.125, 0.25, 0.03],)

ax_m2 = plt.axes([0.55, 0.075, 0.25, 0.03],)
ax_t2 = plt.axes([0.55, 0.125, 0.25, 0.03],)

# Define Slider value
mSlider1 = Slider(ax_m1, 'm1', -5.0, 5.0, valinit=m1, valstep=.01)
tSlider1 = Slider(ax_t1, 't1', -5.0, 5.0, valinit=t1, valstep=.01)

mSlider2 = Slider(ax_m2, 'm2', -5.0, 5.0, valinit=m2, valstep=.01)
tSlider2 = Slider(ax_t2, 't2', -5.0, 5.0, valinit=t2, valstep=.01)



#//////////////////////////////////////////////////////////////////////////////update

y1 = m1*x + t1
a1 = ax.plot(x, y1, lw = 3, alpha = 0.5, color="blue")

y2 = m2*x + t2
a2 = ax.plot(x, y2, lw = 3, alpha = 1, color = "orange")


def update_m1(mSlider1):
    global m1
    m1 = mSlider1
    
def update_t1(tSlider1):
    global t1
    t1 = tSlider1
    
def update_m2(mSlider2):
    global m2
    m2 = mSlider2
    
def update_t2(tSlider2):
    global t2
    t2 = tSlider2

def update_f1(y1):
    global a1
    line = a1.pop(0)
    line.remove()
    y1 = m1*x + t1
    a1 = ax.plot(x, y1, lw = 3, alpha = 0.5, color="blue")

def update_f2(y2):
    global a2
    line = a2.pop(0)
    line.remove()
    y2 = m2*x + t2
    a2 = ax.plot(x, y2, lw = 3, alpha = 1, color = "orange")


mSlider1.on_changed(update_m1,)
tSlider1.on_changed(update_t1,)

mSlider1.on_changed(update_f1,)
tSlider1.on_changed(update_f1,)

mSlider2.on_changed(update_m2,)
tSlider2.on_changed(update_t2,)

mSlider2.on_changed(update_f2,)
tSlider2.on_changed(update_f2,)

#//////////////////////////////////////////////////////////////////////////////

# Set identical scales for both axes
ax.set(xlim=(xmin-1, xmax+1), ylim=(ymin-1, ymax+1), aspect='equal')

# Set bottom and left spines as x and y axes of coordinate system
ax.spines['bottom'].set_position('zero')
ax.spines['left'].set_position('zero')

# Remove top and right spines
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)

# Create 'x' and 'y' labels placed at the end of the axes
ax.set_xlabel('x', size=14, labelpad=-24, x=1.03)
ax.set_ylabel('y', size=14, labelpad=-21, y=1.02, rotation=0)

# Create custom major ticks to determine position of tick labels
x_ticks = np.arange(xmin, xmax+1, ticks_frequency)
y_ticks = np.arange(ymin, ymax+1, ticks_frequency)
ax.set_xticks(x_ticks[x_ticks != 0])
ax.set_yticks(y_ticks[y_ticks != 0])

# Create minor ticks placed at each integer to enable drawing of minor grid
# lines: note that this has no effect in this example with ticks_frequency=1
ax.set_xticks(np.arange(xmin, xmax+1), minor=True)
ax.set_yticks(np.arange(ymin, ymax+1), minor=True)

# Draw major and minor grid lines
ax.grid(which='both', color='grey', linewidth=1, linestyle='-', alpha=0.2)

# Draw arrows
arrow_fmt = dict(markersize=4, color='black', clip_on=False)
ax.plot((1), (0), marker='>', transform=ax.get_yaxis_transform(), **arrow_fmt)
ax.plot((0), (1), marker='^', transform=ax.get_xaxis_transform(), **arrow_fmt)

plt.show()