问题描述
在模拟中使用几个滑块来改变某些属性，我想创建一个ipywidgets。将所有滑块值设置为某些默认值的按钮，有人知道怎么做吗？
from ipywidgets import FloatSlider,IntSlider,IntText,Button
A = FloatSlider(value=4,min=-10,max=20,step=0.1)
B = IntSlider(value=2,min=0,max=8,step=2)
C = IntText()
default_value_button = Button(description='click to set default values')
...
#I want this button to set specific values for A,B,C
#I need its action to be:
A.set_state('value') = 3.7
B.set_state('value') = 4
C.set_state('value') = 547
...
display(A,C,default_value_button)
单击按钮时，我需要设置默认值：
提前感谢您的关注！
解决方法
这是一个简单的实现，只需为小部件设置default_value属性，然后在创建它们时将这些小部件编译到列表中即可。
与此有关的一个问题是，如果您将这些小部件连接到交互功能，则将该值设置为default也将触发交互功能。这可能是您想要的，也可能不是！
from ipywidgets import *
A = FloatSlider(value=4,min=-10,max=20,step=0.1)
B = IntSlider(value=2,min=0,max=8,step=2)
C = IntText()
A.default_value = 3.7
B.default_value = 4
C.default_value = 547
defaulting_widgets = [A,B,C]
default_value_button = Button(description='click to set default values')
def set_default(button):
for widget in defaulting_widgets:
widget.value = widget.default_value
default_value_button.on_click(set_default)
display(A,C,default_value_button)
import numpy as np
from ipywidgets import *
from matplotlib import cm
import matplotlib.pylab as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import axes3d
def hist_3D(xdata,ydata,xtitle='X',ytitle='Y'):
SQUARE_BIN_NUMBER = IntSlider(description="bins",min=5,max=40,value=20)
AZIM = IntSlider(description="azimuth",min=-180,max=180,value=-60,layout=widgets.Layout(width='600px'))
ELEV = IntSlider(description="elevation",min=-90,max=90,value=30,layout=widgets.Layout(height='400px'),orientation='vertical')
VU = Dropdown (options=[('X histogram',1),('Y histogram',2),('XY colored',3),('Random view',4)],value=4,description='options :')
SHADE = Checkbox (description="shade",value=True)
DEFAULT_VALUE_BUTTON = Button(description='default values')
SQUARE_BIN_NUMBER.default_value = 20
AZIM.default_value = -60
ELEV.default_value = 30
VU.default_value = 4
SHADE.default_value = True
defaulting_widgets = [SQUARE_BIN_NUMBER,AZIM,ELEV,VU,SHADE]
def run(square_bin_number,azim,elev,vu=None,shade=True):
if(vu == 1): azim,shade = -90,True
elif(vu == 2): azim,shade = 0,False
elif(vu == 3): azim,90,True
x = np.array(xdata) #turn x,y data into numpy arrays
y = np.array(ydata)
fig = plt.figure(figsize=(10,7)) #create a canvas,tell matplotlib it's 3d
ax = fig.add_subplot(111,projection='3d')
#make histogram stuff - set bins - I choose 20x20 because I have a lot of data
hist,xedges,yedges = np.histogram2d(x,y,bins=(square_bin_number,square_bin_number))
xpos,ypos = np.meshgrid(xedges[:-1]+xedges[1:],yedges[:-1]+yedges[1:],indexing='ij')
#attenetion : meshgrid(indexing must be 'ij' and it's 'xy' by default)
xpos = xpos.flatten()/2.
ypos = ypos.flatten()/2.
zpos = np.zeros_like (xpos)
dx = xedges [1] - xedges [0]
dy = yedges [1] - yedges [0]
dz = hist.flatten()
cmap = cm.get_cmap('jet') # Get desired colormap - you can change this!
max_height = np.max(dz) # get range of colorbars so we can normalize
min_height = np.min(dz)
# scale each z to [0,1],and get their rgb values
rgba = [cmap((k-min_height)/max_height) for k in dz]
ax.bar3d(xpos,ypos,zpos,dx,dy,dz,color=rgba,zsort='average',shade=shade)
ax.view_init(azim=azim,elev=elev)
plt.xlabel(xtitle)
plt.ylabel(ytitle)
# plt.savefig("Your_title_goes_here")
plt.show()
def set_default(button):
for widget in defaulting_widgets:
widget.value = widget.default_value
DEFAULT_VALUE_BUTTON.on_click(set_default)
out = interactive_output(run,{'vu':VU,'square_bin_number':SQUARE_BIN_NUMBER,'azim':AZIM,'elev':ELEV,'shade':SHADE})
display(VU,HBox([out,ELEV]),VBox([AZIM,HBox([SQUARE_BIN_NUMBER,SHADE])]),DEFAULT_VALUE_BUTTON)
A = np.random.multivariate_normal([0,0],np.identity(2),size=10000)
x = A[:,0]
y = A[:,1]
hist_3D(x,y)