// Files seeded into new projects.

const readme = `# stan sample project
`;

const linearStan = `// Bayesian linear regression: y ~ normal(alpha + beta * x, sigma)
data {
  int<lower=0> N;
  vector[N] x;
  vector[N] y;
}
parameters {
  real alpha;
  real beta;
  real<lower=0> sigma;
}
model {
  alpha ~ normal(0, 5);
  beta ~ normal(0, 5);
  sigma ~ normal(0, 2);
  y ~ normal(alpha + beta * x, sigma);
}
generated quantities {
  // posterior predictive draw at x = 6
  real y_at_6 = normal_rng(alpha + beta * 6, sigma);
}
`;

const dataJson = `{
  "N": 20,
  "x": [0.17, 0.41, 0.77, 0.96, 1.23, 1.46, 1.66, 1.8, 2.01, 2.32,
        2.59, 3.05, 3.21, 3.45, 3.61, 3.83, 4.03, 4.52, 4.75, 5.0],
  "y": [2.13, 2.9, 3.51, 3.69, 3.41, 4.05, 4.56, 3.9, 3.5, 5.17,
        6.14, 6.62, 6.55, 7.31, 7.34, 6.33, 8.81, 8.79, 8.56, 9.16]
}
`;

const fitSample = `# A sampling run. This file opens as a form; use the tab context menu to
# edit the raw YAML. Paths are relative to this file.
stan: linear.stan
data: data.json
num_chains: 4
num_warmup: 1000
num_samples: 1000
seed: 42
`;

const quickSample = `# A quicker look: fewer iterations, random seed each run.
stan: linear.stan
data: data.json
num_chains: 2
num_warmup: 200
num_samples: 200
`;

export const sampleWorkspace: Record<string, string> = {
	'/README.md': readme,
	'/linear.stan': linearStan,
	'/data.json': dataJson,
	'/fit.sample': fitSample,
	'/quick.sample': quickSample,
};

const emptyStan = `// Write your Stan program here.
parameters {
  real mu;
}
model {
  mu ~ normal(0, 1);
}
`;

export const emptyWorkspace: Record<string, string> = {
	'/main.stan': emptyStan,
	'/data.json': '{}\n',
	'/fit.sample': `stan: main.stan\ndata: data.json\n`,
};