def testYearly(self):
datestring = 'Yearly'
start_date = datetime.datetime.now()
hydro = Hydro(start_date, datestring)
hydro.tokenize()
self.assertEqual(len(hydro.tokens['all'].tokens), 1)
def testLimit(self):
datestring = "Daily for 100 times"
start_date = datetime.datetime.now()
hydro = Hydro(start_date, datestring)
hydro.tokenize()
self.assertEqual(len(hydro.all_tokens.tokens), 4)
dates = hydro.generate_dates()
self.assertEqual(len(dates), 100)
def testDaily(self):
datestring = 'Daily'
start_date = datetime.datetime.now()
hydro = Hydro(start_date, datestring)
hydro.tokenize()
self.assertEqual(len(hydro.tokens['all'].tokens), 1)
dates = hydro.generate_dates()
self.assertEqual(len(dates), 365)
def testMaximium(self):
"""
We're only allowed to return 365 events for now
"""
datestring = "Daily for 1201 times"
start_date = datetime.datetime.now()
hydro = Hydro(start_date, datestring)
hydro.tokenize()
self.assertEqual(len(hydro.all_tokens.tokens), 4)
dates = hydro.generate_dates()
self.assertEqual(len(dates), 365)
# === Hydro model
# precipitation
from precipitation import precipitation_coefficients
# distribution for the initial model values
from initial import initial
# construct Hydro model
from hydro import Hydro
model = Hydro(precipitation_coefficients,
initial,
dt=10,
integrator='RKSSP',
numbify=0)
# === SPUX
# LIKELIHOOD
# construct Particle Filtering likelihood
from spux.likelihoods.pf import PF
likelihood = PF(particles=[4, 16])
#likelihood = PF (particles=16)
# REPLICATES
# use Replicates aggregator to combine likelihood with multiple data sets
from spux.aggregators.replicates import Replicates
replicates = Replicates()
# SAMPLER
# construct EMCEE sampler
# === BARRIER
from spux import framework
framework.barrier ()
# === MODEL
from hydro import Hydro
from precipitation import precipitation_coefficients
from initial import initial
model = Hydro (precipitation_coefficients, initial, dt=10, integrator='RKSSP', numbify=0)
framework.assign (model)
# === INIT FRAMEWORK
model.attach (workers = None)
from spux.utils.seed import Seed
from spux.utils.sandbox import Sandbox
sandbox = Sandbox ('sandbox-synthesize')
seed = Seed (1)
# setup SPUX framework
framework.setup (sandbox = sandbox, seed = seed, verbosity = 1, outputdir = 'datasets_synthetic')
# init SPUX framework
framework.init ()
