def fbprophet_univariate_best_r() -> float:
"""
:return: Provides best r for a randomly chosen data stream
Takes about 12 hrs to run
"""
mr = MicroReader()
names = mr.get_stream_names()
okay = False
while not okay:
name = random.choice(names)
n_obs = len(mr.get_lagged_values(name=name))
okay = n_obs > PROPHET_META['n_warm'] + 50 and '~' not in name
url = 'https://www.microprediction.org/stream_dashboard.html?stream=' + name.replace(
'.json', '')
print('We will find the best fbprophet hyper-parameters for ' + url)
print('There are ' + str(n_obs) + ' observations in the series.')
print(
"Prophet will be fit for most of them, after a burn_in, and for many different hyper-params. Don't hold your breathe."
)
best_r, best_value, info = optimal_r_for_stream(
f=fbprophet_univariate_r2,
name=name,
k=10,
optimizer=dlib_default_cube,
n_burn=PROPHET_META['n_warm'] + 20,
n_trials=50,
n_dim=2)
pprint(info)
params = prophet_params(r=best_r, dim=2)
pprint(params)
def random_regular(min_len=500):
""" Randomly selected univariate series
:return: y, t, url
"""
mr = MicroReader()
names = mr.get_stream_names()
okay = False
while not okay:
name = random.choice(names)
n_obs = len(mr.get_lagged_values(name=name,count=10000))
okay = n_obs > min_len and '~' not in name
url = 'https://www.microprediction.org/stream_dashboard.html?stream=' +name.replace('.json','')
return name, url
def random_stream_name(min_len=500, exclude_str=None, include_str=None):
""" Randomly selected univariate series
:return: y, t, url
"""
mr = MicroReader()
names = mr.get_stream_names()
okay = False
while not okay:
name = random.choice(names)
n_obs = len(mr.get_lagged_values(name=name, count=10000))
okay = True
if exclude_str is not None and exclude_str in name:
okay = False
if include_str is not None and include_str not in name:
okay = False
if n_obs < min_len:
okay = False
url = 'https://www.microprediction.org/stream_dashboard.html?stream=' + name.replace(
'.json', '')
return name, url
def plot_helicopter_lags():
""" Plot a subset of the SciML helicopter challenge data .. psi only """
mr = MicroReader()
xs = mr.get_lagged_values('helicopter_psi.json')
plt.plot(xs)
def test_imports():
mr = MicroReader()
values = mr.get_lagged_values(name='cop.json')
assert len(values)>500
