Scale cov incalcs (#53)

* fixes #52 scale covariance by dependent vars
* don't need registry in layers
* tested using `Uncertainties.wrap()` by comparing uncertainties for calculated zenith and azimuth

Author: mikofski

carousel/core/calculations.py

@@ -276,6 +276,12 @@ def calc_static(self, formula_reg, data_reg, out_reg, timestep):
                     # split uncertainty and jacobian from return values
                     cov, jac = retval[-2:]
                     retval = retval[:-2]
+                    # scale covariance
+                    scale = np.asarray(
+                        [1 / r.m if isinstance(r, UREG.Quantity) else 1 / r
+                         for r in retval]
+                    )  # use magnitudes if quantities
+                    cov = (np.swapaxes((cov.T * scale), 0, 1) * scale).T
                     nret = len(retval)  # number of return output
                     for m in xrange(nret):
                         a = returns[m]  # name in output registry

carousel/core/layers.py

@@ -27,7 +27,6 @@
 
 import importlib
 import os
-from carousel.core import Registry
 from carousel.core.simulations import SimRegistry
 from carousel.core.data_sources import DataRegistry
 from carousel.core.formulas import FormulaRegistry