ajout de Lagrange

Author: nicob-dev

InitialValueProblem/.idea/InitialValueProblem.iml

@@ -0,0 +1,32 @@
+import numpy as np
+import math
+
+def Lagrange(xData,yData, x):
+    """
+    Lagrange interpolation function is used to aproximate the f(x) value
+
+    @pre : Here length of xData  must be the same for yData
+           xData  : <list>  The known x-points
+           yData  : <list>  The points y associated with a x
+           x      : <Float> The point at which we are looking for the image
+
+    @post : return <Float> The Pn (x) value
+    """
+    # Apply the equation
+    res = 0
+    for i in range(len(xData)):
+        prod = 1
+        for j in range(len(yData)):
+            if(i!=j):
+                prod *= (x-xData[j])/(xData[i]-xData[j])
+        res += prod*yData[i]
+    return res
+
+
+# --------------- EXAMPLE ---------------
+
+# xData = [ -1.2, 0.3, 1.1]
+# yData = [ -5.76, -5.61, -3.69]
+# x = 0
+#
+# print(Lagrange(xData, yData, x))

InitialValueProblem/.idea/inspectionProfiles/profiles_settings.xml

@@ -37,7 +37,7 @@ def LUsolve(a, b, rp):
     then Ux = y using backward substitution.
 
     @pre : a  : <np.array | type=float64> The matrix LU (n x n) from LUdecomp(A)
-           b  : <np.array | type=float32> The matrix b (1 x n)
+           b  : <np.array | type=float64> The matrix b (1 x n)
            rp : <List> indices of the lines that where pivoted in LUdecompRP()
 
     @post : return <np.array> : (1 x n) matrix