Added tests of new nonlinearity class-based code, simulating data from

simple nonlinear function. Closes issue #30.

tests/test_nonlinearities.py

@@ -0,0 +1,55 @@
+"""test_nonlinearities.py
+Test code for pyret's nonlinearities module.
+(C) 2016 The Baccus Lab
+"""
+import numpy as np
+
+from pyret import nonlinearities
+
+def test_sigmoid():
+    """Test the Sigmoid nonlinearity class"""
+    # True parameters
+    thresh = 0.5
+    slope = 2
+    peak = 1.5
+    baseline = 0.2
+    n = 1000        # Number of simulate data points
+    xscale = 2      # Scale factor for input range
+    noise = 0.1     # Standard deviation of AWGN
+
+    # Simulate data
+    x = np.random.randn(n,) * xscale
+    y = nonlinearities.Sigmoid._sigmoid(x, thresh, slope,
+            peak, baseline) + np.random.randn(n,) * noise
+
+    # Fit nonlinearity and compare
+    y_hat = nonlinearities.Sigmoid().fit(x, y).predict(x)
+    norm = (np.linalg.norm(y - y_hat) / np.linalg.norm(y))
+    if (norm > (noise * 1.5)):
+        raise AssertionError("Fitting a Sigmoid nonlinearity seems " + 
+                "to have failed, relative error = {0:#0.3f}".format(norm))
+
+def test_binterp():
+    """Test the Binterp nonlinearity class"""
+    # True parameters
+    thresh = 0.5
+    slope = 2
+    peak = 1.5
+    baseline = 0.2
+    n = 1000        # Number of simulate data points
+    xscale = 2      # Scale factor for input range
+    noise = 0.1     # Standard deviation of AWGN
+    nbins = 25      # Number of bins in the Binterp nonlienarity
+
+    # Simulate data
+    x = np.random.randn(n,) * xscale
+    y = nonlinearities.Sigmoid._sigmoid(x, thresh, slope,
+            peak, baseline) + np.random.randn(n,) * noise
+
+    # Fit nonlinearity and compare
+    y_hat = nonlinearities.Binterp(nbins).fit(x, y).predict(x)
+    norm = (np.linalg.norm(y - y_hat) / np.linalg.norm(y))
+    if (norm > (noise * 1.5)):
+        raise AssertionError("Fitting a Sigmoid nonlinearity seems " + 
+                "to have failed, relative error = {0:#0.3f}".format(norm))
+