Fix rebin error when nan present in raw data

LiquidDiffract/core/data_utils.py

@@ -21,6 +21,9 @@ def rebin_data(x, y, dx=0.02, x_lim=None, extrapolate_mode='fill'):
         x_rebin = np.arange(x_lim[0], x_lim[1], dx)
     else:
         x_rebin = np.arange(0, x[-1], dx)
+    # Check for any nans in y and remove via interpolation
+    if np.isnan(np.sum(y)):
+        y = interp_nan(y)
     if extrapolate_mode == 'fill':
         f_interp = scipy.interpolate.interp1d(x, y,
                                               kind='cubic',

tests/core/test_data_utils.py

@@ -114,14 +114,17 @@ def test_rebin_data(self):
 
     def test_rebin_nan(self):
         # Test nan values in y have little effect
-        x = np.arange(0, 12, 0.001)
+        x = np.arange(0, 12.0, 0.001)
         y = np.cos(x)
         # Inject single np.nan
         y[500] = np.nan
         expected_rebin_y = np.cos(np.arange(0, 12, 0.02))
         _, rebin_y = data_utils.rebin_data(x, y, dx=0.02)
         # Check interpolation in rebinning accurate
-        self.assertArrayEqual(rebin_y, expected_rebin_y)
+        # y[500] --> rebin_y[25] (0.02/0.001 = 20)
+        # Check arrays equal skipping interpolated value
+        self.assertFloatArrayEqual(np.delete(rebin_y, 25), np.delete(expected_rebin_y, 25))
+        self.assertFloatEqual(rebin_y[25], expected_rebin_y[25], rtol=1e-6)
 
     def test_rebin_extrapolate_fill(self):
         x = np.arange(0.34, 12.0, 0.02)