Issue/176 amplitude dif

.zenodo.json

@@ -33,6 +33,11 @@
       "orcid": "0000-0003-1001-0707",
       "affiliation": "Department of Physics and Astronomy, Aarhus University, DK",
       "name": "Tronsgaard, René"
+    },
+    {
+      "orcid": "0000-0003-3287-5250",
+      "affiliation": "Department of Astronomy and the DiRAC Institute, University of Washington, Seattle, WA, USA",
+      "name": "Caplar, Neven"
     }
   ],
   "license": "MIT",

news/176.doc

@@ -0,0 +1 @@
+Clarified in documentation that sigma argument is optional in quasisep kernels.

src/tinygp/kernels/quasisep.py

@@ -390,7 +390,10 @@ class SHO(Quasisep):
     Args:
         omega: The parameter :math:`\omega`.
         quality: The parameter :math:`Q`.
-        sigma: The parameter :math:`\sigma`.
+        sigma (optional): The parameter :math:`\sigma`. Defaults to a value of
+            1. Specifying the explicit value here provides a slight performance
+            boost compared to independently multiplying the kernel with a
+            prefactor.
     """
 
     omega: JAXArray
@@ -464,7 +467,10 @@ class Exp(Quasisep):
 
     Args:
         scale: The parameter :math:`\ell`.
-        sigma: The parameter :math:`\sigma`.
+        sigma (optional): The parameter :math:`\sigma`. Defaults to a value of
+            1. Specifying the explicit value here provides a slight performance
+            boost compared to independently multiplying the kernel with a
+            prefactor.
     """
 
     scale: JAXArray
@@ -498,7 +504,10 @@ class Matern32(Quasisep):
 
     Args:
         scale: The parameter :math:`\ell`.
-        sigma: The parameter :math:`\sigma`.
+        sigma (optional): The parameter :math:`\sigma`. Defaults to a value of
+            1. Specifying the explicit value here provides a slight performance
+            boost compared to independently multiplying the kernel with a
+            prefactor.
     """
     scale: JAXArray
     sigma: JAXArray = field(default_factory=lambda: jnp.ones(()))
@@ -540,7 +549,10 @@ class Matern52(Quasisep):
 
     Args:
         scale: The parameter :math:`\ell`.
-        sigma: The parameter :math:`\sigma`.
+        sigma (optional): The parameter :math:`\sigma`. Defaults to a value of
+            1. Specifying the explicit value here provides a slight performance
+            boost compared to independently multiplying the kernel with a
+            prefactor.
     """
 
     scale: JAXArray
@@ -602,7 +614,10 @@ class Cosine(Quasisep):
 
     Args:
         scale: The parameter :math:`\ell`.
-        sigma: The parameter :math:`\sigma`.
+        sigma (optional): The parameter :math:`\sigma`. Defaults to a value of
+            1. Specifying the explicit value here provides a slight performance
+            boost compared to independently multiplying the kernel with a
+            prefactor.
     """
     scale: JAXArray
     sigma: JAXArray = field(default_factory=lambda: jnp.ones(()))