Update pymc_experimental/marginal_model.py

jessegrabowski · ricardoV94 · web-flow · commit 02d4ed6e4ab9 · 2023-11-21T21:25:34.000+01:00
observation -&gt; emission in comments

Co-authored-by: Ricardo Vieira &lt;28983449+ricardoV94@users.noreply.github.com&gt;
diff --git a/pymc_experimental/marginal_model.py b/pymc_experimental/marginal_model.py
@@ -537,7 +537,7 @@ def eval_logp(x):
         chain_dummy: pt.moveaxis(pt.broadcast_to(domain, (*values[0].shape, domain.size)), -1, 0)
     }
 
-    # This is a (k, T) matrix of logp terms, one for each state - observation pair
+    # This is a (k, T) matrix of logp terms, one for each state - emission pair
     vec_logp_emission = vectorize_graph(tuple(logp_value_dict.values()), sub_dict)
 
     # Step 2: Compute the transition probabilities

Original file line number	Diff line number	Diff line change
`@@ -537,7 +537,7 @@ def eval_logp(x):`
`537`	`537`	`chain_dummy: pt.moveaxis(pt.broadcast_to(domain, (*values[0].shape, domain.size)), -1, 0)`
`538`	`538`	`}`
`539`	`539`
`540`		`- # This is a (k, T) matrix of logp terms, one for each state - observation pair`
	`540`	`+ # This is a (k, T) matrix of logp terms, one for each state - emission pair`
`541`	`541`	`vec_logp_emission = vectorize_graph(tuple(logp_value_dict.values()), sub_dict)`
`542`	`542`
`543`	`543`	`# Step 2: Compute the transition probabilities`