我正在使用matplotlib滑块，类似于this demo。滑块目前使用2个小数位，并且“感觉”非常连续（尽管它们必须在某种程度上是离散的）。我能决定它们的离散程度吗？整数步数？0.1级台阶？0.5？我的google fu失败了。
最佳答案
如果只需要整数值，则在创建滑块（例如valfmt）时只需传入适当的valfmt='%0.0f'。
但是，如果您需要非整数的inversals，则每次都需要手动设置文本值。尽管如此，即使这样做了，滑动条仍将顺利进行，并且不会像离散间隔那样“感觉”。
下面是一个例子：
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.widgets import Slider
class ChangingPlot(object):
def __init__(self):
self.inc = 0.5
self.fig, self.ax = plt.subplots()
self.sliderax = self.fig.add_axes([0.2, 0.02, 0.6, 0.03],
axisbg='yellow')
self.slider = Slider(self.sliderax, 'Value', 0, 10, valinit=self.inc)
self.slider.on_changed(self.update)
self.slider.drawon = False
x = np.arange(0, 10.5, self.inc)
self.ax.plot(x, x, 'ro')
self.dot, = self.ax.plot(self.inc, self.inc, 'bo', markersize=18)
def update(self, value):
value = int(value / self.inc) * self.inc
self.dot.set_data([[value],[value]])
self.slider.valtext.set_text('{}'.format(value))
self.fig.canvas.draw()
def show(self):
plt.show()
p = ChangingPlot()
p.show()
如果您想让滑块“感觉”完全像离散值，可以将其子类化。关键效果由
matplotlib.widgets.Slider在这种情况下，您可以这样做：
class DiscreteSlider(Slider):
"""A matplotlib slider widget with discrete steps."""
def __init__(self, *args, **kwargs):
"""Identical to Slider.__init__, except for the "increment" kwarg.
"increment" specifies the step size that the slider will be discritized
to."""
self.inc = kwargs.pop('increment', 0.5)
Slider.__init__(self, *args, **kwargs)
def set_val(self, val):
discrete_val = int(val / self.inc) * self.inc
# We can't just call Slider.set_val(self, discrete_val), because this
# will prevent the slider from updating properly (it will get stuck at
# the first step and not "slide"). Instead, we'll keep track of the
# the continuous value as self.val and pass in the discrete value to
# everything else.
xy = self.poly.xy
xy[2] = discrete_val, 1
xy[3] = discrete_val, 0
self.poly.xy = xy
self.valtext.set_text(self.valfmt % discrete_val)
if self.drawon:
self.ax.figure.canvas.draw()
self.val = val
if not self.eventson:
return
for cid, func in self.observers.iteritems():
func(discrete_val)
作为使用它的完整示例：
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.widgets import Slider
class ChangingPlot(object):
def __init__(self):
self.inc = 0.5
self.fig, self.ax = plt.subplots()
self.sliderax = self.fig.add_axes([0.2, 0.02, 0.6, 0.03],
facecolor='yellow')
self.slider = DiscreteSlider(self.sliderax, 'Value', 0, 10,
increment=self.inc, valinit=self.inc)
self.slider.on_changed(self.update)
x = np.arange(0, 10.5, self.inc)
self.ax.plot(x, x, 'ro')
self.dot, = self.ax.plot(self.inc, self.inc, 'bo', markersize=18)
def update(self, value):
self.dot.set_data([[value],[value]])
self.fig.canvas.draw()
def show(self):
plt.show()
class DiscreteSlider(Slider):
"""A matplotlib slider widget with discrete steps."""
def __init__(self, *args, **kwargs):
"""Identical to Slider.__init__, except for the "increment" kwarg.
"increment" specifies the step size that the slider will be discritized
to."""
self.inc = kwargs.pop('increment', 0.5)
Slider.__init__(self, *args, **kwargs)
self.val = 1
def set_val(self, val):
discrete_val = int(val / self.inc) * self.inc
# We can't just call Slider.set_val(self, discrete_val), because this
# will prevent the slider from updating properly (it will get stuck at
# the first step and not "slide"). Instead, we'll keep track of the
# the continuous value as self.val and pass in the discrete value to
# everything else.
xy = self.poly.xy
xy[2] = discrete_val, 1
xy[3] = discrete_val, 0
self.poly.xy = xy
self.valtext.set_text(self.valfmt % discrete_val)
if self.drawon:
self.ax.figure.canvas.draw()
self.val = val
if not self.eventson:
return
for cid, func in self.observers.items():
func(discrete_val)
p = ChangingPlot()
p.show()
关于python - 我可以使matplotlib滑块更加离散吗？，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/13656387/