matplotlib
diff --git a/‎doc/api/api_changes/2017-06-11-DB_magnitude_spectrum.rst
Copy file name to clipboard
+31Lines changed: 31 additions & 0 deletions b/‎doc/api/api_changes/2017-06-11-DB_magnitude_spectrum.rst
Copy file name to clipboard
+31Lines changed: 31 additions & 0 deletions
diff --git a/‎lib/matplotlib/axes/_axes.py
Copy file name to clipboardExpand all lines: lib/matplotlib/axes/_axes.py
+1-2Lines changed: 1 addition & 2 deletions b/‎lib/matplotlib/axes/_axes.py
Copy file name to clipboardExpand all lines: lib/matplotlib/axes/_axes.py
+1-2Lines changed: 1 addition & 2 deletions
diff --git a/‎lib/matplotlib/mlab.py
Copy file name to clipboardExpand all lines: lib/matplotlib/mlab.py
+2-2Lines changed: 2 additions & 2 deletions b/‎lib/matplotlib/mlab.py
Copy file name to clipboardExpand all lines: lib/matplotlib/mlab.py
+2-2Lines changed: 2 additions & 2 deletions
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/magnitude_spectrum_freqs_dB.png
Copy file name to clipboard
-1.02 KB b/‎lib/matplotlib/tests/baseline_images/test_axes/magnitude_spectrum_freqs_dB.png
Copy file name to clipboard
-1.02 KB
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/magnitude_spectrum_freqs_linear.png
Copy file name to clipboard
89 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/magnitude_spectrum_freqs_linear.png
Copy file name to clipboard
89 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/magnitude_spectrum_noise_dB.png
Copy file name to clipboard
136 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/magnitude_spectrum_noise_dB.png
Copy file name to clipboard
136 Bytes
diff --git a/‎lib/matplotlib/tests/baseline_images/test_axes/magnitude_spectrum_noise_linear.png
Copy file name to clipboard
63 Bytes b/‎lib/matplotlib/tests/baseline_images/test_axes/magnitude_spectrum_noise_linear.png
Copy file name to clipboard
63 Bytes
@@ -0,0 +1,31 @@
+Correct scaling of :func:`magnitude_spectrum()`
+```````````````````````````````````````````````
+
+The functions :func:`matplotlib.mlab.magnitude_spectrum()` and :func:`matplotlib.pyplot.magnitude_spectrum()` implicitly assumed the sum
+of windowing function values to be one. In Matplotlib and Numpy the
+standard windowing functions are scaled to have maximum value of one,
+which usually results in a sum of the order of n/2 for a n-point
+signal. Thus the amplitude scaling :func:`magnitude_spectrum()` was
+off by that amount when using standard windowing functions (`Bug 8417
+<https://github.com/matplotlib/matplotlib/issues/8417>`_ ). Now the
+behavior is consistent with :func:`matplotlib.pyplot.psd()` and
+:func:`scipy.signal.welch()`. The following example demonstrates the
+new and old scaling::
+
+    import matplotlib.pyplot as plt
+    import numpy as np
+    
+    tau, n = 10, 1024  # 10 second signal with 1024 points
+    T = tau/n  # sampling interval
+    t = np.arange(n)*T
+    
+    a = 4  # amplitude
+    x = a*np.sin(40*np.pi*t)  # 20 Hz sine with amplitude a
+    
+    # New correct behavior: Amplitude at 20 Hz is a/2
+    plt.magnitude_spectrum(x, Fs=1/T, sides='onesided', scale='linear')
+    
+    # Original behavior: Amplitude at 20 Hz is (a/2)*(n/2) for a Hanning window
+    w = np.hanning(n)  # default window is a Hanning window
+    plt.magnitude_spectrum(x*np.sum(w), Fs=1/T, sides='onesided', scale='linear')
+
@@ -6666,8 +6666,7 @@ def magnitude_spectrum(self, x, Fs=None, Fc=None, window=None,
 
         scale : [ 'default' | 'linear' | 'dB' ]
             The scaling of the values in the *spec*.  'linear' is no scaling.
-            'dB' returns the values in dB scale.  When *mode* is 'density',
-            this is dB power (10 * log10).  Otherwise this is dB amplitude
+            'dB' returns the values in dB scale, i.e., the dB amplitude
             (20 * log10). 'default' is 'linear'.
 
         Fc : integer
 
@@ -727,12 +727,12 @@ def _spectral_helper(x, y=None, NFFT=None, Fs=None, detrend_func=None,
     elif mode == 'psd':
         result = np.conj(result) * result
     elif mode == 'magnitude':
-        result = np.abs(result)
+        result = np.abs(result) / np.abs(windowVals).sum()
     elif mode == 'angle' or mode == 'phase':
         # we unwrap the phase later to handle the onesided vs. twosided case
         result = np.angle(result)
     elif mode == 'complex':
-        pass
+        result /= np.abs(windowVals).sum()
 
     if mode == 'psd':