def config(*animate):
from myutil import quickui
GPRegrTypes = (
('constant',None),
('linear',None),
('quadratic',None),
)
GPKernels = (
('absolute_exponential','exp(-theta|d|)'),
('squared_exponential','exp(-theta|d|^2)'),
#'generalized_exponential',
('cubic',None),
('linear',None),
)
def GPconv(regr=None,corr=None,**ka):
return GP(regr=GPRegrTypes[regr][0],corr=GPKernels[corr][0],**ka)
Q = quickui.cbook
return quickui.configuration(
Q.Ctransf(partial(dict,logscale=False,nsample=100,clevel=.95,gpmean=False)),
('syst',dict(anchor=True),Q.Ctransf(partial(GPconv,regr=2,corr=1,theta0=.1,thetaL_r=.01,thetaU_r=100.,nugget=.01,random_start=1)),
datasection(),
('regr',dict(accept=Q.i,tooltip='Regression type'),Q.Cbase.Set(options=GPRegrTypes)),
('corr',dict(accept=Q.i,tooltip='GP kernel'),Q.Cbase.Set(options=GPKernels)),
('nugget',dict(accept=Q.i,tooltip='Tychonov regularisation'),Q.Cbase.LogScalar(vmin=.0001,vmax=1000)),
('theta0',dict(accept=Q.i,tooltip='Larger means faster decrease of prior correlation when distance increases'),Q.Cbase.LogScalar(vmin=.001,vmax=10.)),
('thetaL_r',dict(accept=Q.i,tooltip='Ratio to theta0 of lower bound of parameter space exploration'),Q.Cbase.LogScalar(vmin=.001,vmax=1.)),
('thetaU_r',dict(accept=Q.i,tooltip='Ratio to theta0 of upper bound of parameter space exploration'),Q.Cbase.LogScalar(vmin=1.,vmax=1000.)),
('random_start',dict(accept=Q.i,tooltip='number of MLE repeats from randomly chosen initialisation'),Q.Cbase.LinScalar(vtype=int,vmin=1,vmax=10)),
),
('clevel',dict(accept=Q.i,tooltip='Confidence level'),Q.Cbase.LinScalar(vtype=float,vmin=.9,vmax=.9999)),
('gpmean',dict(accept=Q.i,sel=None,tooltip='Check to show GP mean (linear combination of basis functions)'),Q.Cbase.Boolean(),),
('nsample',dict(accept=Q.i,tooltip='Number of test samples'),Q.Cbase.LinScalar(vtype=int,vmin=50,vmax=500)),
('logscale',dict(accept=Q.i,sel=None,tooltip='Check for x-axis in logscale'),Q.Cbase.Boolean(),),
)
def config(*animate):
from animate import cfg_anim
from myutil import quickui
ffmt = '{0:.3f}'.format
Q = quickui.cbook
return quickui.configuration(
Q.Ctransf(dict,multi=True),
('syst',dict(sel=None),
Q.Ctransf(
partial(
RandomWalk,
N=400,
)
),
('stepg',dict(tooltip='Specification of the normal 0-mean random step'),
Q.Ctransf(
partial(
bvn,
vx=3.1,
vy=2.8,
cor=.5
)
),
('vx',dict(accept=Q.i),
Q.Cbase.LinScalar(vmin=.1,vmax=1.,nval=1000,vtype=float,fmt=ffmt)
),
('vy',dict(accept=Q.i),
Q.Cbase.LinScalar(vmin=.1,vmax=1.,nval=1000,vtype=float,fmt=ffmt)
),
('cor',dict(accept=Q.i),
Q.Cbase.LinScalar(vmin=0.,vmax=1.,nval=1000,vtype=float,fmt=ffmt)
)
),
('N',dict(accept=Q.i),
Q.Cbase.LinScalar(step=1,vmin=100,vmax=1000,vtype=int)
),
),
('animate',dict(sel=False))+
cfg_anim(
*animate,
modifier=dict(
save=dict(
filename='randwalk.mp4',
metadata=dict(
title='A random walk',
),
),
)
),
)
def config(*animate):
from animate import cfg_anim
from myutil import quickui
ffmt = '{:.1f}'.format
Q = quickui.cbook
return quickui.configuration(
Q.Ctransf(
partial(
dict,
srate=25.,
taild=1.,
maxtime=infty,
),
multi=True,
),
('srate',dict(sel=None,accept=Q.i,tooltip='sample rate in Hz'),
Q.Cbase.LinScalar(vmin=10,vmax=50,nval=1000,vtype=float,fmt=ffmt)
),
('taild',dict(sel=None,accept=Q.i,tooltip='shadow length in s'),
Q.Cbase.LinScalar(step=1,vmin=0,vmax=10,vtype=float,fmt=ffmt)
),
('syst',dict(sel=None),
Q.Ctransf(
partial(
Pendulum,
L=1.,
G=9.81,
)
),
('G',dict(accept=Q.i,tooltip='gravity acceleration in m/s^2'),
Q.Cbase.LinScalar(vmin=1.,vmax=20.,nval=1000,vtype=float,fmt=ffmt)
),
('L',dict(accept=Q.i,tooltip='length of pendulum in m'),
Q.Cbase.LinScalar(vmin=.1,vmax=10.,nval=1000,vtype=float,fmt=ffmt)
),
),
('ini',dict(),
Q.Ctransf(
partial(
Pendulum.makestate,
theta=179.,
)
),
('theta',dict(accept=Q.i,tooltip='initial angle of pendulum in deg'),
Q.Cbase.LinScalar(vmin=-180.,vmax=180.,nval=1000,vtype=float,fmt=ffmt)
),
),
('maxtime',dict(accept=Q.i,tooltip='duration of simulation in s'),
Q.Cbase.LinScalar(step=1.,vmin=10.,vmax=3600.,vtype=float,fmt=ffmt)
),
('animate',dict(sel=False))+
cfg_anim(
*animate,
modifier=dict(
timer=dict(
interval=40.,
),
save=dict(
filename='pendulum1.mp4',
metadata=dict(
title='A simple pendulum simulation',
),
),
)
),
)
def config(*animate):
from animate import cfg_anim
from myutil import quickui
krange = range(1,4)
ffmt = '{0:.2f}'.format
Q = quickui.cbook
def normalise(a): return a/sum(a)
def c_component():
return (
Q.Ctransf(
partial(
bvn,
mx=10*rand(),
my=10*rand(),
vx=10*rand(),
vy=10*rand(),
cor=rand(),
)
),
('mx',dict(accept=Q.i),
Q.Cbase.LinScalar(vmin=0.,vmax=10.,nval=100,vtype=float,fmt=ffmt)
),
('my',dict(accept=Q.i),
Q.Cbase.LinScalar(vmin=0.,vmax=10.,nval=100,vtype=float,fmt=ffmt)
),
('vx',dict(accept=Q.i),
Q.Cbase.LinScalar(vmin=0.,vmax=10.,nval=100,vtype=float,fmt=ffmt)
),
('vy',dict(accept=Q.i),
Q.Cbase.LinScalar(vmin=0.,vmax=10.,nval=100,vtype=float,fmt=ffmt)
),
('cor',dict(accept=Q.i),
Q.Cbase.LinScalar(vmin=-1.,vmax=1.,nval=100,vtype=float,fmt=ffmt)
),
)
def c_weight():
return (
Q.Cbase.LinScalar(vmin=0.,vmax=10.,nval=100,vtype=float,fmt=ffmt),
)
return quickui.configuration(
Q.Ctransf(dict,multi=True),
('syst',dict(sel=None),
Q.Ctransf(
partial(
Kmeans,
K=5,
)
),
('data',dict(sel=None),
Q.Ctransf(
partial(
mixture,
N=1000,
)
),
('N',dict(accept=Q.i,tooltip='Number of points'),
Q.Cbase.LinScalar(vmin=50,vmax=20000,nval=1000,vtype=int)
),
('weights',dict(tooltip='Weights of the generating mixture'),
Q.Ccomp(lambda l: normalise(array(Q.selectv(l))),
defaultdict(lambda: 10*uniform())
)
)+tuple(('w'+str(k),dict(accept=Q.i))+c_weight() for k in krange),
('comp',dict(tooltip='Components of the generating mixture'),
Q.Ccomp(Q.selectv,None)
)+tuple(('c'+str(k),dict(anchor=True))+c_component() for k in krange),
),
('K',dict(accept=Q.i,tooltip='Number of clusters'),
Q.Cbase.LinScalar(vmin=2,vmax=20,step=1,vtype=int)
),
),
('animate',dict(sel=False))+
cfg_anim(
*animate,
modifier=dict(
save=dict(
filename='kmeans.mp4',
metadata=dict(
title='An execution of the kmeans algorithm',
),
),
)
),
)
def test(*animate):
from animate import cfg_anim
from myutil import quickui
ffmt = '{:.1f}'.format
Q = quickui.cbook
return quickui.configuration(
Q.Ctransf(
partial(
dict,
srate=25.,
taild=1.,
maxtime=infty,
),
multi=True,
),
('srate',dict(sel=None,accept=Q.i,tooltip='sample rate in Hz'),
Q.Cbase.LinScalar(vmin=10,vmax=50,nval=1000,vtype=float,fmt=ffmt)
),
('taild',dict(sel=None,accept=Q.i,tooltip='shadow length in s'),
Q.Cbase.LinScalar(step=1,vmin=0,vmax=10,vtype=float)
),
('syst',dict(sel=None),
Q.Ctransf(
partial(
DoublePendulum,
M1=5.,
L1=2.,
M2=.1,
L2=1.,
G=9.81,
)
),
('G',dict(accept=Q.i,tooltip='acceleration due to gravity in m/s^2'),
Q.Cbase.LinScalar(vmin=1.,vmax=20.,nval=1000,vtype=float,fmt=ffmt)
),
('M1',dict(accept=Q.i,tooltip='mass of pendulum 1 in kg'),
Q.Cbase.LinScalar(vmin=.05,vmax=20.,nval=1000,vtype=float,fmt=ffmt)
),
('L1',dict(accept=Q.i,tooltip='length of pendulum 1 in m'),
Q.Cbase.LinScalar(vmin=.1,vmax=10.,nval=1000,vtype=float,fmt=ffmt)
),
('M2',dict(accept=Q.i,tooltip='mass of pendulum 2 in kg'),
Q.Cbase.LinScalar(vmin=.05,vmax=20.,nval=1000,vtype=float,fmt=ffmt)
),
('L2',dict(accept=Q.i,tooltip='length of pendulum 2 in m'),
Q.Cbase.LinScalar(vmin=.1,vmax=10.,nval=1000,vtype=float,fmt=ffmt)
),
),
('ini',dict(),
Q.Ctransf(
partial(
DoublePendulum.makestate,
theta1=180.,
theta2=1.,
)
),
('theta1',dict(accept=Q.i,tooltip='initial angle of pendulum 1 in deg'),
Q.Cbase.LinScalar(vmin=-180.,vmax=180.,nval=1000,vtype=float,fmt=ffmt)
),
('theta2',dict(accept=Q.i,tooltip='initial angle of pendulum 2 in deg'),
Q.Cbase.LinScalar(vmin=-180.,vmax=180.,nval=1000,vtype=float,fmt=ffmt)
),
),
('maxtime',dict(accept=Q.i,tooltip='duration of simulation in s'),
Q.Cbase.LinScalar(step=1.,vmin=10.,vmax=3600.,vtype=float,fmt=ffmt)
),
('animate',dict(sel=False))+
cfg_anim(
*animate,
modifier=dict(
timer=dict(
interval=40.,
),
save=dict(
filename='pendulum2.mp4',
extra_args = ('-cache','1000000'),
metadata=dict(
title='A double pendulum simulation',
),
),
)
),
)
