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Least-square-method/exponential.py

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+welcome="""
+#*#*#*#*#*#*#*#*#**#*#*#*#**#*#*#*#**#*#*#*#*#*#**#*#*#*#**#*#*#*#**#*#
+#*                                                                   #*
+#*                        Curve Fitting                              #*
+#*                              By                                   #*
+#*                     Least Square Method                           #*
+#*       Find the Exponential Curve that BEST fits for your data     #*
+#*                     Credit- Monirul Shawon                        #*
+#*                                                                   #*
+#*#*#*#*#*#*#*#*#**#*#*#*#**#*#*#*#**#*#*#*#*#*#**#*#*#*#**#*#*#*#**#*#
+"""
+print(welcome)
+
+import numpy as np
+import math
+from tabulate import tabulate
+x=[]
+y=[]
+try:
+    n=int(input("How many number of sets you've got there? \n n= "))
+    print('-'*70)
+    print("Let, y=ae^(bx) or Y=A+Bx where Y=log10(y) , A=log10(a) and B=blog10(e) ")
+    print('-'*70)
+    #taking x values
+    print("\nInput values of x: ")
+    for i in range(1,n+1):
+        xnum=float(input(f" x{i} = "))
+        x.append(xnum)
+    #taking y values
+    print("\nInput values of y:")
+    for j in range(1,n+1):
+        ynum=float(input(f" y{j} = "))
+        y.append(ynum)
+    #making x square row
+    squarex=[a*a for a in x]
+    #making Y=log10(y) row
+    Y=[math.log10(b) for b in y]
+    #making x*y row
+    multi=[a*b for a,b in zip(x,Y)]
+    #table
+    table=[(p,q,r,s,t) for p,q,r,s,t in zip(x,y,Y,squarex,multi)]
+    headers=['x','y','Y=log10(y)','x^2','xY']
+    print(tabulate(table,headers,tablefmt="pretty"))
+    #table summation
+    sumx=sum(x)
+    sumy=sum(y)
+    sumY=sum(Y)
+    sumsquarex=sum(squarex)
+    sumxY=sum(multi)
+    #table2
+    table2=[(sumx,sumy,sumY,sumsquarex,sumxY)]
+    headers2=['∑x','∑y','∑Y','∑x^2','∑xY']
+    print(tabulate(table2,headers2,tablefmt="pretty"))
+
+    print(f"\nEquation 1 is: {sumY} = {n} A + {sumx} B")
+    print(f"Equation 2 is: {sumxY} = {sumx} A + {sumsquarex} B")
+    #solve liner equations
+    M=np.array([[n,sumx],[sumx,sumsquarex]])
+    N=np.array([sumY,sumxY])
+    X=np.linalg.solve(M,N)
+    #solve a and b
+    a=math.pow(10,X[0])
+    b=X[1]/(math.log10(math.e))
+    print(f"Hence, the required curve is: y={a} e^({b} x)")
+except:
+    print("\nNo.. input is not a number. It's a string.")
+    print("Please input number to continue your calculation")