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WIP: Fix single precision #197

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WIP: Fix single precision #197

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a964cb6
Fix single precision default filter
Sep 22, 2020
9358139
Add missing conversion
Sep 22, 2020
688493d
Merge master
Oct 16, 2020
95b60cf
Add blank lines back
Oct 16, 2020
5bf6ebd
Remove damped linear trend
Oct 16, 2020
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4 changes: 2 additions & 2 deletions src/models/arima.jl
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Expand Up @@ -216,7 +216,7 @@ function default_filter(model::ARIMA)
num_arma_states = max(model.order.p, model.order.q + 1)
r = model.order.d + num_arma_states
a1 = zeros(Fl, r)
P1 = 1e6 .* Matrix{Fl}(I, r, r)
P1 = Fl(1e6) .* Matrix{Fl}(I, r, r)
skip_llk_instants = model.order.d
steadystate_tol = Fl(1e-5)
return UnivariateKalmanFilter(a1, P1, skip_llk_instants, steadystate_tol)
Expand Down Expand Up @@ -303,4 +303,4 @@ function reinstantiate(model::ARIMA, y::Vector{Fl}) where Fl
order = (model.order.p, model.order.d, model.order.q)
return ARIMA(y, order)
end
has_exogenous(::ARIMA) = false
has_exogenous(::ARIMA) = false
4 changes: 2 additions & 2 deletions src/models/basicstructural.jl
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Expand Up @@ -49,7 +49,7 @@ function default_filter(model::BasicStructural)
Fl = typeof_model_elements(model)
steadystate_tol = Fl(1e-5)
a1 = zeros(Fl, num_states(model))
P1 = 1e6 .* Matrix{Fl}(I, num_states(model), num_states(model))
P1 = Fl(1e6) .* Matrix{Fl}(I, num_states(model), num_states(model))
return UnivariateKalmanFilter(a1, P1, num_states(model), steadystate_tol)
end
function initial_hyperparameters!(model::BasicStructural)
Expand Down Expand Up @@ -87,4 +87,4 @@ end
function reinstantiate(model::BasicStructural, y::Vector{Fl}) where Fl
return BasicStructural(y, model.seasonality)
end
has_exogenous(::BasicStructural) = false
has_exogenous(::BasicStructural) = false
2 changes: 1 addition & 1 deletion src/models/damped_lineartrend.jl
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Expand Up @@ -27,7 +27,7 @@ end
function default_filter(::DampedLinearTrend{Fl}) where Fl
steadystate_tol = 1e-5
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a1 = zeros(Fl, 2)
P1 = 1e6 .* Matrix{Fl}(I, 2, 2)
P1 = Fl(1e6) .* Matrix{Fl}(I, 2, 2)
return UnivariateKalmanFilter(a1, P1, 0, steadystate_tol)
end
function initial_hyperparameters!(model::DampedLinearTrend{Fl}) where Fl
Expand Down
2 changes: 1 addition & 1 deletion src/models/locallineartrend.jl
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Expand Up @@ -50,7 +50,7 @@ function default_filter(model::LocalLinearTrend)
Fl = typeof_model_elements(model)
steadystate_tol = 1e-5
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a1 = zeros(Fl, 2)
P1 = 1e6 .* Matrix{Fl}(I, 2, 2)
P1 = Fl(1e6) .* Matrix{Fl}(I, 2, 2)
return UnivariateKalmanFilter(a1, P1, 2, steadystate_tol)
end
function initial_hyperparameters!(model::LocalLinearTrend)
Expand Down
11 changes: 9 additions & 2 deletions test/models/basicstructural.jl
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Expand Up @@ -3,7 +3,7 @@
log_air_passengers = log.(air_passengers.passengers)

@test has_fit_methods(BasicStructural)

model = BasicStructural(log_air_passengers, 12)
fit!(model)
# Runned on Python statsmodels
Expand All @@ -15,4 +15,11 @@
# simualting
scenarios = simulate_scenarios(model, 10, 10_000)
test_scenarios_adequacy_with_forecast(forec, scenarios)
end

@testset "Basic structural with single precision" begin
log_ap32 = Float32.(log_air_passengers)
model = BasicStructural(log_ap32, 12)
@test model.system.Z == Float32[1.0; 0.0; 1.0; zeros(10)]
fit!(model)
end
end