fixed bounds in _drop_peak_overlap

Author: ryanhammonds

fooof/objs/fit.py

@@ -816,7 +816,7 @@ def _fit_peaks(self, flat_iter):
             max_ind = np.argmax(flat_iter)
             max_height = flat_iter[max_ind]
 
-            # Stop searching for peaks peaks once drops below height threshold
+            # Stop searching for peaks once height drops below height threshold
             if max_height <= self.peak_threshold * np.std(flat_iter):
                 break
 
@@ -1033,7 +1033,7 @@ def _drop_peak_overlap(self, guess):
         guess = sorted(guess, key=lambda x: float(x[0]))
 
         # Calculate standard deviation bounds for checking amount of overlap
-        bounds = [[peak[0] - peak[2] * self._gauss_overlap_thresh, peak[0],
+        bounds = [[peak[0] - peak[2] * self._gauss_overlap_thresh,
                    peak[0] + peak[2] * self._gauss_overlap_thresh] for peak in guess]
 
         # Loop through peak bounds, comparing current bound to that of next peak
@@ -1164,7 +1164,7 @@ def _prepare_data(freqs, power_spectrum, freq_range, spectra_dim=1, verbose=True
             freqs, power_spectrum = trim_spectrum(freqs, power_spectrum, freq_range)
 
         # Check if freqs start at 0 and move up one value if so
-        #   Aperiodic fit gets an inf is freq of 0 is included, which leads to an error
+        #   Aperiodic fit gets an inf if freq of 0 is included, which leads to an error
         if freqs[0] == 0.0:
             freqs, power_spectrum = trim_spectrum(freqs, power_spectrum, [freqs[1], freqs.max()])
             if verbose: