fix exp2

experiments/exp2/run_inference_galaxy_images.py

@@ -6,8 +6,9 @@
 
 import jax.numpy as jnp
 import typer
-from jax import jit, random, vmap
+from jax import Array, jit, random, vmap
 from jax._src.prng import PRNGKeyArray
+from jax.scipy import stats
 
 from bpd import DATA_DIR
 from bpd.chains import run_sampling_nuts, run_warmup_nuts
@@ -17,10 +18,35 @@
     get_target_images,
     get_true_params_from_galaxy_params,
     loglikelihood,
-    logprior,
     logtarget,
     sample_target_galaxy_params_simple,
 )
+from bpd.prior import ellip_prior_e1e2
+
+
+def logprior(
+    params: dict[str, Array],
+    *,
+    sigma_e: float,
+    sigma_x: float = 0.5,  # pixels
+    flux_bds: tuple = (-1.0, 9.0),
+    hlr_bds: tuple = (0.01, 5.0),
+) -> Array:
+    prior = jnp.array(0.0)
+
+    f1, f2 = flux_bds
+    prior += stats.uniform.logpdf(params["lf"], f1, f2 - f1)
+
+    h1, h2 = hlr_bds
+    prior += stats.uniform.logpdf(params["hlr"], h1, h2 - h1)
+
+    prior += stats.norm.logpdf(params["x"], loc=0.0, scale=sigma_x)
+    prior += stats.norm.logpdf(params["y"], loc=0.0, scale=sigma_x)
+
+    e1e2 = jnp.stack((params["e1"], params["e2"]), axis=-1)
+    prior += jnp.log(ellip_prior_e1e2(e1e2, sigma=sigma_e))
+
+    return prior
 
 
 def sample_prior(