fix: rewrite helper functions to have option to do derivative or not

src/emgdecompy/emgdecompy.py

@@ -252,7 +252,7 @@ def normalize(w):
     return w
 
 
-def apply_contrast_fun_router(w, fun=der_skew):
+def apply_contrast_fun_router(w, fun=skew, der=False):
     """
     Takes first derivitive and applies contrast function to w with map()
     for Step 2a of fixed point algorithm
@@ -273,32 +273,28 @@ def apply_contrast_fun_router(w, fun=der_skew):
     Example
     --------
         >>> w = np.array([1, 2, 3])
-        >>> fun = der_skew
+        >>> fun = skew
         >>> apply_contrast_fun_router(w, fun)
         >>> array([1, 4, 9])
     """
 
-    # an_array = np.array([1, 2, 3])
-
-    # def double(x):
-    #    return x * 2
-
-    # mapped_array = double(an_array)
-    # print(mapped_array)
-
-    rtn = fun(w)
+    rtn = fun(w, der)
     return rtn
 
 
-def der_skew(x):
+def skew(x, der=False):
     """
-    Takes first derivitive and applies contrast function to w
-    function = x^3 / 3
+    Applies contrast function (if der=False) or
+    first derivative of contrast function (if der=True)
+    to w
+    skew = x^3 / 3
 
     Parameters
     ----------
         x: float
             number to apply contrast function to
+        der: boolean
+            whether to apply derivative (or base version)
 
     Returns
     -------
@@ -313,20 +309,27 @@ def der_skew(x):
     """
 
     # first derivitive of x^3/3 = x^2
-    rtn = x ** 2
+    if der == True:
+        rtn = x ** 2
+    else:
+        rtn = (x ** 3) / 3
 
     return rtn
 
 
-def der_log_cosh(x):
+def log_cosh(x, der=False):
     """
-    Takes first derivitive and applies contrast function to w
+    Applies contrast function (if der=False) or
+    first derivative of contrast function (if der=True)
+    to w
     function = log(cosh(x))
 
     Parameters
     ----------
         x: float
             number to apply contrast function to
+        der: boolean
+            whether to apply derivative (or base version)
 
     Returns
     -------
@@ -335,26 +338,33 @@ def der_log_cosh(x):
 
     Example
     --------
-        >>> x = 0.5
-        >>> der_log_cosh(x)
-        >>> 0.46211715726000974
+        >>> x = 4
+        >>> log_cosh(x)
+        >>> 16
     """
 
     # first derivitive of log(cosh(x)) = tanh(x)
-    rtn = np.tanh(x)
+    if der == True:
+        rtn = np.tanh(x)
+    else:
+        rtn = np.log(np.cosh(x))
 
     return rtn
 
 
-def der_exp_sq(x):
+def exp_sq(x, der=False):
     """
-    Takes first derivitive and applies contrast function to w
+    Applies contrast function (if der=False) or
+    first derivative of contrast function (if der=True)
+    to w
     function = exp((-x^2/2))
 
     Parameters
     ----------
         x: float
             number to apply contrast function to
+        der: boolean
+            whether to apply derivative (or base version)
 
     Returns
     -------
@@ -370,7 +380,10 @@ def der_exp_sq(x):
 
     # first derivitive of exp((-x^2/2)) = -e^(-x^2/2) x
     pwr_x = -(x ** 2) / 2
-    rtn = -(np.exp(pwr_x) * x)
+    if der == True:
+        rtn = -(np.exp(pwr_x) * x)
+    else:
+        rtn = np.exp(pwr_x)
 
     return rtn