From c7a258aa1d7e16b5e9e5a6a738d27853676ef2c1 Mon Sep 17 00:00:00 2001
From: Markus Rosenstihl <markus.rosenstihl@pkm.tu-darmstadt.de>
Date: Thu, 8 Jan 2015 16:56:44 +0100
Subject: [PATCH] removed redundant implementations of fit functions (hav-neg,
 conductiviety, etc.)

---
 data/Container.py    | 28 +++++-----------------------
 libmath/functions.py |  2 +-
 2 files changed, 6 insertions(+), 24 deletions(-)

diff --git a/data/Container.py b/data/Container.py
index 71eb450..77211a1 100644
--- a/data/Container.py
+++ b/data/Container.py
@@ -21,19 +21,12 @@ class Conductivity(BaseContainer):
         self.color = QColor("blue")
         self.id_label = "Cond."
         self.id_string = "cond"
-
         self.param_number = 3
+
+
     def function(self, p ,x):
         return functions.cond_cmplx(p,x)
 
-    # def function( self, p, x ):
-    #     om = 2*np.pi*x
-    #     sgma, isgma, n = p
-    #     cond = sgma/(om**n)+isgma/(1j*om**n)  # Jonscher (Universal Dielectric Response: e",e' prop sigma/omega**n
-    #     cplx = np.array([cond.real, -cond.imag])
-    #     return cplx
-
-
 
 class PowerComplex(BaseContainer):
     def __init__( self, plt_real=None, plt_imag=None, limits=None ):
@@ -45,11 +38,7 @@ class PowerComplex(BaseContainer):
         self.param_number = 2
 
     def function( self, p, x ):
-        om = 2*np.pi*x
-        sgma, n = p
-        power = sgma/(om*1j)**n
-        cplx = np.array([power.real, -power.imag])
-        return cplx
+        return functions.power_cmplx(p, x)
 
 
 class Static(BaseContainer):
@@ -62,10 +51,7 @@ class Static(BaseContainer):
         self.param_number = 1
 
     def function( self, p, x ):
-        eps_inf = p[0]
-        static = np.ones((2, x.size))*eps_inf
-        static[1, :] *= 0  # set imag part zero
-        return static
+        return functions.static_cmplx(p, x)
 
 
 class Peak(BaseContainer):
@@ -81,11 +67,7 @@ class Peak(BaseContainer):
         self.param_number = 4
 
     def function( self, p, x ):
-        eps, t, a, b = p
-        om = 2*np.pi*x
-        hn = eps/(1+(1j*om*t)**a)**b
-        cplx = np.array([hn.real, -hn.imag])
-        return cplx
+        return functions.hn(p, x)
 
 
 class YAFF(BaseContainer):
diff --git a/libmath/functions.py b/libmath/functions.py
index dff9027..3b0e607 100644
--- a/libmath/functions.py
+++ b/libmath/functions.py
@@ -54,7 +54,7 @@ class HavNegCmplx(Function):
         self.set_num_paramters(4)
 
 
-def hn(x, p):
+def hn(p, x):
     om = 2*np.pi*x
     #hn = om*1j
     eps, t, a, b = p