Create typos.yaml

.pre-commit-config.yaml

@@ -36,3 +36,9 @@ repos:
         args: ['--baseline', '.secrets.baseline',
                '--exclude-files', 'model/docs/']
         exclude: package.lock.json
+####
+# Typos
+-   repo: https://github.com/crate-ci/typos
+    rev: v1.19.0
+    hooks:
+    -   id: typos

model/docs/getting-started.ipynb

@@ -17,7 +17,7 @@
     "\n",
     "`pyrenew` has five main components:\n",
     "\n",
-    "- Utilitiy and math functions,\n",
+    "- Utility and math functions,\n",
     "- The `processes` sub-module,\n",
     "- The `observations` sub-module,\n",
     "- The `latent` sub-module, and\n",

model/src/pyrenew/metaclass.py

@@ -96,7 +96,7 @@ def sample(
     ) -> tuple:
         """Sample method of the process
 
-        The method desing in the class should have two dictionaries:
+        The method design in the class should have two dictionaries:
         `random_variables` and `constants`.
 
         - `randon_variables`: This dictionary contains any data that sample

model/src/pyrenew/model/hospitalizations.py

@@ -135,7 +135,7 @@ def sample(
         if constants is None:
             constants = dict()
 
-        # Getting the basline quantities from the basic model
+        # Getting the baseline quantities from the basic model
         Rt, infections, *_ = self.basic_renewal.sample(
             constants=constants,
             random_variables=random_variables,

model/src/pyrenew/observation/negativebinomial.py

@@ -23,7 +23,7 @@ def __init__(
 
         Parameters
         ----------
-        concentration_prior : dist.Distribution | nummbers.nums
+        concentration_prior : dist.Distribution | numbers.nums
             Numpyro distribution from which to sample the positive concentration
             parameter of the negative binomial. This parameter is sometimes
             called k, phi, or the "dispersion" or "overdispersion" parameter,

model/src/pyrenew/process/simplerandomwalk.py

@@ -10,7 +10,7 @@ class SimpleRandomWalkProcess(RandomVariable):
     """
     Class for a Markovian
     random walk with an a
-    abitrary step distribution
+    arbitrary step distribution
     """
 
     def __init__(