Simplified code

wafo/transform/models.py

@@ -387,19 +387,24 @@ class TrLinear(TrCommon2):
 
     """
 
-    def _dat2gauss(self, x, *xi):
-        sratio = atleast_1d(self.ysigma / self.sigma)
-        y = (atleast_1d(x) - self.mean) * sratio + self.ymean
+    def _transform(self, ymean, ysigma, xmean, xsigma, x, xi):
+        sratio = atleast_1d(ysigma / xsigma)
+        y = (atleast_1d(x) - xmean) * sratio + ymean
         if len(xi) > 0:
-            y = [y, ] + [ix * sratio for ix in xi]
+            y = [y] + [ix * sratio for ix in xi]
         return y
 
+    def _dat2gauss(self, x, *xi):
+        ysigma, xsigma = self.ysigma, self.sigma
+        ymean, xmean = self.ymean, self.mean
+
+        return self._transform(ymean, ysigma, xmean, xsigma, x, xi)
+
     def _gauss2dat(self, y, *yi):
-        sratio = atleast_1d(self.sigma / self.ysigma)
-        x = (atleast_1d(y) - self.ymean) * sratio + self.mean
-        if len(yi) > 0:
-            x = [x, ] + [iy * sratio for iy in yi]
-        return x
+        ysigma, xsigma = self.ysigma, self.sigma
+        ymean, xmean = self.ymean, self.mean
+
+        return self._transform(xmean, xsigma, ymean, ysigma, y, yi)
 
 
 class TrOchi(TrCommon2):
@@ -524,6 +529,11 @@ class TrOchi(TrCommon2):
         mean2 = self._phat[5]
         return ga, gb, sigma2, mean2
 
+    def _forward(self, g, xn, gab, idx):
+        if gab != 0:
+            np.put(g, idx, (-expm1(-gab * xn[idx])) / gab)
+        return g
+
     def _dat2gauss(self, x, *xi):
         if len(xi) > 0:
             raise ValueError('Transforming derivatives is not implemented!')
@@ -537,16 +547,17 @@ class TrOchi(TrCommon2):
         igm, = where(xn < 0)
 
         g = xn.copy()
-
-        if ga != 0:
-            np.put(g, igp, (-expm1(-ga * xn[igp])) / ga)
-
-        if gb != 0:
-            np.put(g, igm, (-expm1(-gb * xn[igm])) / gb)
+        g = self._forward(g, xn, ga, igp)
+        g = self._forward(g, xn, gb, igm)
 
         g.shape = shape0
         return (g - mean2) * self.ysigma / sigma2 + self.ymean
 
+    def _backward(self, xn, gab, idx):
+        if gab != 0:
+            np.put(xn, idx, -log1p(-gab * xn[idx]) / gab)
+        return xn
+
     def _gauss2dat(self, y, *yi):
         if len(yi) > 0:
             raise ValueError('Transforming derivatives is not implemented!')
@@ -561,11 +572,8 @@ class TrOchi(TrCommon2):
         igp, = where(0 <= xn)
         igm, = where(xn < 0)
 
-        if ga != 0:
-            np.put(xn, igp, -log1p(-ga * xn[igp]) / ga)
-
-        if gb != 0:
-            np.put(xn, igm, -log1p(-gb * xn[igm]) / gb)
+        xn = self._backward(xn, ga, igp)
+        xn = self._backward(xn, gb, igm)
 
         xn.shape = yn.shape
         return sigma * xn + mean