From 8672c46f6d69bee4d4119f3eeb395b521e7b6521 Mon Sep 17 00:00:00 2001
From: Joel Leja <joel.leja@gmail.com>
Date: Wed, 3 Jun 2020 17:15:35 -0400
Subject: [PATCH] PhotoCal model for correlated photometric noise

---
 prospect/fitting/fitting.py    |  3 ++-
 prospect/likelihood/kernels.py | 16 ++++++++++++----
 2 files changed, 14 insertions(+), 5 deletions(-)

diff --git a/prospect/fitting/fitting.py b/prospect/fitting/fitting.py
index 7fb61739..b1a273f5 100644
--- a/prospect/fitting/fitting.py
+++ b/prospect/fitting/fitting.py
@@ -99,7 +99,8 @@ def lnprobfn(theta, model=None, obs=None, sps=None, noise=(None, None),
         sigma_spec = spec_noise.construct_covariance(**vectors)
     if phot_noise is not None:
         phot_noise.update(**model.params)
-        vectors.update({'phot_unc': obs.get('maggies_unc', None)})
+        vectors.update({'phot_unc': obs.get('maggies_unc', None),
+                        'phot': obs.get('maggies', None)})
 
     # --- Generate mean model ---
     try:
diff --git a/prospect/likelihood/kernels.py b/prospect/likelihood/kernels.py
index 790f40b8..c5bda9fc 100644
--- a/prospect/likelihood/kernels.py
+++ b/prospect/likelihood/kernels.py
@@ -1,6 +1,6 @@
 import numpy as np
 
-__all__ = ["Kernel", "Uncorrelated", "ExpSquared", "Matern"]
+__all__ = ["Kernel", "Uncorrelated", "ExpSquared", "Matern", "PhotoCal"]
 
 
 class Kernel(object):
@@ -94,8 +94,16 @@ def construct_kernel(self, metric):
         return Sigma
 
 
-class Outliers(Kernel):
-    kernel_params = ['amplitude', 'location']
+class PhotoCal(Kernel):
 
+    ndim = 2
+    npars = 2
+    kernel_params = ['amplitude', 'filter_names']
+    
     def construct_kernel(self, metric):
-        raise(NotImplementedError)
+        """ This adds correlated noise in specified bands of photometry
+        """
+        k = np.array([f in self.params["filter_names"] for f in metric])
+        K = k[:, None] * k[None, :]     # select off-diagonal elements
+        return K * self.params["amplitude"]**2
+