def pmd_exog_compare(f, k=1):
from timemachines.skaters.evaluation import evaluate_mean_absolute_error
from timemachines.data.real import hospital_with_exog
y, a = hospital_with_exog(k=k)
y0 = [yi[0] for yi in y]
r = 0.1 # Doesn't matter?
err1 = evaluate_mean_absolute_error(f=f, k=k, y=y0, r=r, n_burn=250)
err2 = evaluate_mean_absolute_error(f=f, k=k, y=y, r=r, n_burn=250)
err3 = evaluate_mean_absolute_error(f=f, k=k, y=y, r=r, a=a, n_burn=250)
errlv = evaluate_mean_absolute_error(f=last_value,
k=k,
y=y,
r=r,
a=a,
n_burn=250)
print('----------------')
print("Error w/o exogenous = " + str(err1))
print("Error w exogenous = " + str(err2))
print("Error w exo + known = " + str(err3))
print("Error last val cache = " + str(errlv))
# Assert immutability of k, dimensions
if s['y']:
assert len(y) == len(s['y'][0])
assert k == s['k']
if s['a']:
assert len(a) == len(s['a'][0])
if y is None:
return None, s, None
else:
s['y'].append(y)
if a is not None:
s['a'].append(a)
if len(s['y']) > max(2*k+5,PROPHET_META['n_warm']):
x, x_std, _, _ = prophet_iskater_factory(y=s['y'], k=k, a=s['a'], freq=freq, n_max=n_max)
else:
x = [y[0]] * k
x_std = [1.0] * k
return x, x_std, s
if __name__ == '__main__':
from timemachines.data.real import hospital_with_exog
from timemachines.skaters.evaluation import evaluate_mean_absolute_error
k = 3
y, a = hospital_with_exog(k=k, n=100, offset=True)
f = fbprophet_skater_factory
err2 = evaluate_mean_absolute_error(f=f, k=k, y=y, a=a, n_burn=50)
print(err2)
def slowly_moving_average(y: Y_TYPE,
s,
k: int,
a: A_TYPE = None,
t: T_TYPE = None,
e: E_TYPE = None):
return moving_average_r1(y=y, s=s, k=k, a=a, t=t, e=e, r=0.95)
def quickly_moving_average(y: Y_TYPE,
s,
k: int,
a: A_TYPE = None,
t: T_TYPE = None,
e: E_TYPE = None):
return moving_average_r1(y=y, s=s, k=k, a=a, t=t, e=e, r=0.75)
BASIC_SKATERS = [last_value, slowly_moving_average, quickly_moving_average]
BASIC_R1_SKATERS = [moving_average_r1]
if __name__ == '__main__':
from timemachines.data.real import hospital_with_exog
from timemachines.skaters.evaluation import evaluate_mean_absolute_error
k = 3
y, a = hospital_with_exog(k=k)
f = moving_average_r1
err1 = evaluate_mean_absolute_error(f=f, k=k, y=y, a=a, r=0.9, n_burn=50)