added functions-class and class descriptions

plotfitpy/composer.py

+# Class for composing functions
 import numpy as np #Liefert wichtige Rechenfunktionen und numpy-arrays; vergleichsweise schnelle Befehle
 import uncertainties as uc #Rechnen mit Größen, die fehlerbehaftet sind.
 from uncertainties import ufloat as uf

plotfitpy/fitODR.py

+# Class for integrated Fit+Plot Functions
+import numpy as np #Liefert wichtige Rechenfunktionen und numpy-arrays; vergleichsweise schnelle Befehle
+import uncertainties as uc #Rechnen mit Größen, die fehlerbehaftet sind.
+import matplotlib.pyplot as plt
+from scipy.odr import *
+import uncertainties.unumpy as unp
+unv=unp.nominal_values
+usd=unp.std_devs
+
+def fitOdrXYun(func, x, y, sx = None, sy = None, startW = [1]):
+    data = RealData(x, y, sx, sy)
+    func_model = Model(func)
+    odr = ODR(data, func_model, beta0 = startW)
+    out = odr.run()
+    
+    for index, item in enumerate(out.beta):
+        print(out.beta[index], '\t', out.sd_beta[index])
+        
+    out.pprint() #zum Debuggen nutzlich (wenn Fit nicht konvergiert)
+    d = (max(x)-min(x))/20
+    x_fit = np.linspace(min(x)-d, max(x)+d, 200)
+    y_fit = func(out.beta, x_fit)
+    
+    plt.errorbar(x, y, sy, sx, linestyle='None', fmt='.', capsize=5, linewidth=2, zorder = 5)
+    plt.plot(x_fit,y_fit, "--", alpha=1, zorder = 6)
+    return out.beta, out.sd_beta
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plotfitpy/funcs.py

+# Functions used to fit
+
+def getAllFunctions():
+    inspect.getmembers(self, predicate=inspect.ismethod)
+
+def constFunc(p, x):
+    (c) = p
+    return 0*x +c
+
+def linFunc(p, x):
+    (m, c) = p
+    return m*x + c
+
+def quadFunc(p, x)
+    (m, x0, c)
+    return m*(x-x0)**2 + c
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