diff --git a/py4DSTEM/process/wholepatternfit/wpf.py b/py4DSTEM/process/wholepatternfit/wpf.py
index f206004b4..5d4a4e91f 100644
--- a/py4DSTEM/process/wholepatternfit/wpf.py
+++ b/py4DSTEM/process/wholepatternfit/wpf.py
@@ -7,6 +7,8 @@
     WPFModelType,
     Parameter,
 )
+from py4DSTEM.data import RealSlice
+from py4DSTEM.process.strain.latticevectors import get_strain_from_reference_g1g2
 
 from typing import Optional
 import numpy as np
@@ -448,7 +450,7 @@ def accept_mean_CBED_fit(self):
 
     def get_lattice_maps(self) -> list[RealSlice]:
         """
-        Get the fitted reciprical lattice vectors refined at each scan point.
+        Get the fitted reciprocal lattice vectors refined at each scan point.
 
         Returns
         -------
@@ -482,6 +484,68 @@ def get_lattice_maps(self) -> list[RealSlice]:
 
         return g_maps
 
+    def get_strain_maps(
+        self,
+    ) -> list[RealSlice]:
+        """
+        Calculate a strain map from the the fitted reciprocal lattice vectors
+        refined at each scan point.  Currently we output strain maps aligned to the
+        coordinate (qx,qy) directions, and we assume a median reference lattice.
+
+        TODO -allow rotation of Q w.r.t. R coordinate space.
+             -pass in reference lattice, or a mask to the reference ROI.
+
+        Returns
+        -------
+        strain_maps: list[RealSlice]
+            RealSlice objects containing the strain data as a function of scan positions,
+            for each lattice fit in the whole pattern fitting model.
+        """
+        assert hasattr(self, "fit_data"), "Please run fitting first!"
+
+        lattices = [m for m in self.model if WPFModelType.LATTICE in m.model_type]
+        strain_maps = []
+
+        for lat in lattices:
+            # Construct the stack of lattice vectors
+            g1g2_map = RealSlice(
+                np.stack(
+                    [
+                        self.fit_data.data[lat.params["ux"].offset],
+                        self.fit_data.data[lat.params["uy"].offset],
+                        self.fit_data.data[lat.params["vx"].offset],
+                        self.fit_data.data[lat.params["vy"].offset],
+                        np.logical_and(
+                            self.fit_metrics["status"].data
+                            >= 0,  # negative status indicates fit error
+                            self.fit_metrics["nfev"].data > 0,
+                        ),
+                    ],
+                    axis=0,
+                ),
+                slicelabels=["g1x", "g1y", "g2x", "g2y", "mask"],
+                name=lat.name,
+            )
+
+            # Get the reference lattice vectors
+            # TODO - update this to allow other refs, ROI, etc.
+            mask = (g1g2_map.get_slice("mask").data).astype("bool")
+            g1_ref = (
+                np.median(g1g2_map.get_slice("g1x").data[mask]),
+                np.median(g1g2_map.get_slice("g1y").data[mask]),
+            )
+            g2_ref = (
+                np.median(g1g2_map.get_slice("g2x").data[mask]),
+                np.median(g1g2_map.get_slice("g2y").data[mask]),
+            )
+
+            # calculate strain
+            strain_map = get_strain_from_reference_g1g2(g1g2_map, g1_ref, g2_ref)
+            strain_map.name = g1g2_map.name + " strain map"
+            strain_maps.append(strain_map)
+
+        return strain_maps
+
     def _setup_static_data(self):
         """
         Generate basic data that each model can access during the fitting routine