Simplified code

wafo/transform/models.py

@@ -12,7 +12,7 @@ from numpy import (sqrt, atleast_1d, abs, imag, sign, where, cos, arccos, ceil,
                    expm1, log1p, pi)
 import numpy as np
 import warnings
-from .core import TrCommon, TrData
+from wafo.transform.core import TrCommon, TrData
 __all__ = ['TrHermite', 'TrLinear', 'TrOchi']
 
 _EPS = np.finfo(float).eps
@@ -529,50 +529,41 @@ class TrOchi(TrCommon2):
             np.put(x1, idx, -fun(-gab * x2[idx]) / gab)
         return x1
 
-    def _backward(self, xn, y2, gab, idx):
+    def _backward(self, yn):
-        return self._transform(log1p, xn, y2, gab, idx)
+        ga, gb, sigma2, mean2 = self._get_par()
-
+        y2 = sigma2 * yn.ravel() + mean2
-    def _forward(self, y2, xn, gab, idx):
+        igp, = where(0 <= y2)
-        return self._transform(expm1, y2, xn, gab, idx)
+        igm, = where(y2 < 0)
+        xn = y2.copy()
+        xn = self._transform(log1p, xn, y2, ga, igp)
+        xn = self._transform(log1p, xn, y2, gb, igm)
+        return xn
 
-    def _dat2gauss(self, x, *xi):
+    def _forward(self, xn):
-        if len(xi) > 0:
-            raise ValueError('Transforming derivatives is not implemented!')
         ga, gb, sigma2, mean2 = self._get_par()
-        mean = self.mean
+        y2 = xn.copy()
-        sigma = self.sigma
-        xn = atleast_1d(x)
-        shape0 = xn.shape
-        xn = (xn.ravel() - mean) / sigma
         igp, = where(0 <= xn)
         igm, = where(xn < 0)
+        y2 = self._transform(expm1, y2, xn, ga, igp)
+        y2 = self._transform(expm1, y2, xn, gb, igm)
+        return (y2 - mean2) / sigma2
 
-        y2 = xn.copy()
+    def _dat2gauss(self, x, *xi):
-        y2 = self._forward(y2, xn, ga, igp)
+        if len(xi) > 0:
-        y2 = self._forward(y2, xn, gb, igm)
+            raise ValueError('Transforming derivatives is not implemented!')
 
-        y2.shape = shape0
+        xn = (atleast_1d(x) - self.mean) / self.sigma
-        return (y2 - mean2) * self.ysigma / sigma2 + self.ymean
+        shape0 = xn.shape
+        yn = np.reshape(self._forward(xn.ravel()), shape0)
+        return yn * self.ysigma + self.ymean
 
     def _gauss2dat(self, y, *yi):
         if len(yi) > 0:
             raise ValueError('Transforming derivatives is not implemented!')
-
-        ga, gb, sigma2, mean2 = self._get_par()
-        mean = self.mean
-        sigma = self.sigma
-
         yn = (atleast_1d(y) - self.ymean) / self.ysigma
-        y2 = sigma2 * yn.ravel() + mean2
+        shape0 = yn.shape
-
+        xn = np.reshape(self._backward(yn.ravel()), shape0)
-        igp, = where(0 <= y2)
+        return xn * self.sigma + self.mean
-        igm, = where(y2 < 0)
-        xn = y2.copy()
-        xn = self._backward(xn, y2, ga, igp)
-        xn = self._backward(xn, y2, gb, igm)
-
-        xn.shape = yn.shape
-        return sigma * xn + mean
 
 
 def main():
@@ -590,7 +581,7 @@ def main():
 
 if __name__ == '__main__':
     if True:  # False: #
-        import doctest
+        from wafo.testing import test_docstrings
-        doctest.testmod()
+        test_docstrings(__file__)
     else:
         main()