Fix DiffractionPattern k values/vectors

freud/diffraction.pyx

@@ -67,6 +67,7 @@ cdef class DiffractionPattern(_Compute):
     cdef unsigned int _frame_counter
     cdef double _box_matrix_scale_factor
     cdef double[:] _view_orientation
+    cdef double _k_scale_factor
     cdef cbool _k_values_cached
     cdef cbool _k_vectors_cached
 
@@ -130,7 +131,7 @@ cdef class DiffractionPattern(_Compute):
         """Zoom, shear, and scale diffraction intensities.
 
         Args:
-            img ((``grid_size//zoom, grid_size//zoom``) :class:`numpy.ndarray`):
+            img ((``grid_size, grid_size``) :class:`numpy.ndarray`):
                 Array of diffraction intensities.
             box (:class:`~.box.Box`):
                 Simulation box.
@@ -218,8 +219,6 @@ cdef class DiffractionPattern(_Compute):
         view_orientation = freud.util._convert_array(
             view_orientation, (4,), np.double)
 
-        grid_size = int(self.grid_size / zoom)
-
         # Compute the box projection matrix
         inv_shear = self._calc_proj(view_orientation, system.box)
 
@@ -232,7 +231,7 @@ cdef class DiffractionPattern(_Compute):
         xy += 0.5
         xy %= 1
         im, _, _ = np.histogram2d(
-            xy[:, 0], xy[:, 1], bins=np.linspace(0, 1, grid_size+1))
+            xy[:, 0], xy[:, 1], bins=np.linspace(0, 1, self.grid_size+1))
 
         # Compute FFT and convolve with Gaussian
         cdef double complex[:, :] diffraction_fft
@@ -259,8 +258,7 @@ cdef class DiffractionPattern(_Compute):
         if not self._called_compute:
             # Create a 1D axis of k-vector magnitudes
             self._k_values_orig = np.fft.fftshift(np.fft.fftfreq(
-                n=self.output_size,
-                d=1/self.output_size))
+                n=self.output_size))
 
             # Create a 3D meshgrid of k-vectors with shape
             # (output_size, output_size, 3)
@@ -271,6 +269,7 @@ cdef class DiffractionPattern(_Compute):
         # lazy evaluation of k-values and k-vectors
         self._box_matrix_scale_factor = np.max(system.box.to_matrix())
         self._view_orientation = view_orientation
+        self._k_scale_factor = 2 * np.pi * self.output_size / (self._box_matrix_scale_factor * zoom)
         self._k_values_cached = False
         self._k_vectors_cached = False
 
@@ -298,8 +297,7 @@ cdef class DiffractionPattern(_Compute):
     def k_values(self):
         """(``output_size``, ) :class:`numpy.ndarray`: k-values."""
         if not self._k_values_cached:
-            self._k_values = np.asarray(
-                self._k_values_orig) / self._box_matrix_scale_factor
+            self._k_values = np.asarray(self._k_values_orig) * self._k_scale_factor
             self._k_values_cached = True
         return np.asarray(self._k_values)
 
@@ -312,7 +310,7 @@ cdef class DiffractionPattern(_Compute):
         if not self._k_vectors_cached:
             self._k_vectors = rowan.rotate(
                 self._view_orientation,
-                self._k_vectors_orig) / self._box_matrix_scale_factor
+                self._k_vectors_orig) * self._k_scale_factor
             self._k_vectors_cached = True
         return np.asarray(self._k_vectors)