Bring last code block in line with the image.
Code from
@@ -305,14 +305,17 @@ a maximum amount of independent information. It is able to recover
::
>>> # Generate sample data
+ >>> import numpy as np
+ >>> from scipy import signal
>>> time = np.linspace(0, 10, 2000)
>>> s1 = np.sin(2 * time) # Signal 1 : sinusoidal signal
>>> s2 = np.sign(np.sin(3 * time)) # Signal 2 : square signal
- >>> S = np.c_[s1, s2]
+ >>> s3 = signal.sawtooth(2 * np.pi * time) # Signal 3: saw tooth signal
+ >>> S = np.c_[s1, s2, s3]
>>> S += 0.2 * np.random.normal(size=S.shape) # Add noise
>>> S /= S.std(axis=0) # Standardize data
>>> # Mix data
- >>> A = np.array([[1, 1], [0.5, 2]]) # Mixing matrix
+ >>> A = np.array([[1, 1, 1], [0.5, 2, 1], [1.5, 1, 2]]) # Mixing matrix
>>> X = np.dot(S, A.T) # Generate observations
>>> # Compute ICA
