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more_curves = [1810, 2225, 3015]
with curve_spin_model:
    pm.set_data({'spin': more_curves})
    post_pred = pm.sample_posterior_predictive(trace, samples=1000)

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df = pd.DataFrame(dict(y=np.array([2, 4, 2, 0, 4])))

with pm.Model() as glm:
    x = np.array([0.3, 1.1, 0.6, -0.2, 3.3])
    pm.glm.GLM.from_formula('y ~ x', data=df, family=pm.glm.families.Poisson())

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traces = {}

for year in years:
    with curve_spin_model:
        year_data = curveball_data.query('year==@year')
        pm.set_data({'spin': year_data.spin_rate, 
                    'swing_miss': year_data.miss})
        traces[year] = pm.sample(1000, tune=2000,
                                 cores=2, progressbar=False)

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with pm.Model() as curve_spin_model:

    spin = pm.Data('spin', curveball_data['spin_rate'])
    β = pm.Normal('β', shape=2)
    
    θ = β[0] + β[1]*(spin/1000)
    
    swing_miss = pm.Data('swing_miss', curveball_data['miss'])
    miss = pm.Bernoulli('miss', pm.invlogit(θ), observed=swing_miss)

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