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Author: Eslick

pyomo/contrib/sensitivity_toolbox/pynumero.py

@@ -62,7 +62,7 @@ def get_dsdp_dfdp(model, theta):
     Returns
     -------
     scipy.sparse.csc_matrix, csc_matrix, ComponentMap, ComponentMap
-        ds/dp (ns by np), df/dp (1 by np), row map, column map.
+        ds/dp (ns + np by np), df/dp (1 by np), row map, column map.
         The column map maps Pyomo variables p to columns and the
         row map maps Pyomo variables s to rows.
     """
@@ -101,10 +101,7 @@ def get_dsdp_dfdp(model, theta):
 
     # Add independent variables to the rows as the end
     dsdp = scipy.sparse.vstack(
-        [
-            dsdp,
-            scipy.sparse.identity(len(column_map), format="csc"),
-        ]
+        [dsdp, scipy.sparse.identity(len(column_map), format="csc")]
     )
     n = len(row_map)
     for p, i in column_map.items():

pyomo/contrib/sensitivity_toolbox/tests/test_pynumero.py

@@ -83,7 +83,6 @@ def test_dsdp_dfdp_pyomo_nlp(self):
         np.testing.assert_almost_equal(dsdp[rmap[m.p1], cmap[m.p1]], 1.0)
         np.testing.assert_almost_equal(dsdp[rmap[m.p2], cmap[m.p1]], 0.0)
 
-
         # if x1 = 2 * p1 and x2 = p2 then
         #   df/dp1 = 6 p1**2 + p2 = 45.0
         #   df/dp2 = 3 p2 + p1 = 85.0