"""
Interval arithmetic demo: estimating error of numerical Taylor series.

This module can be run interactively with

    python taylor.py

"""
from __future__ import print_function

from mpmath import *

def taylor(x, n):
    print("-"*75)
    t = x = mpi(x)
    s = 1
    print("adding 1")
    print(s, "\n")
    s += t
    print("adding x")
    print(s, "\n")
    for k in range(2, n+1):
        t = (t * x) / k
        s += t
        print("adding x^%i / %i! ~= %s" % (k, k, t.mid))
        print(s, "\n")
    print("-"*75)
    return s

# Note: this should really be computed using interval arithmetic too!
def remainder(x, n):
    xi = max(0, x)
    r = exp(xi) / factorial(n+1)
    r = r * x**(n+1)
    return abs(r)

def exponential(x, n):
    """
    Compute exp(x) using n terms of the Taylor series for exp using
    intervals, and print detailed error analysis.
    """
    t = taylor(x, n)
    r = remainder(x, n)
    expx = exp(x)
    print("Correct value of exp(x):    ", expx)
    print()
    print("Computed interval:          ")
    print(t)
    print()
    print("Computed value (midpoint):  ", t.mid)
    print()
    print("Estimated rounding error:   ", t.delta)
    print("Estimated truncation error: ", r)
    print("Estimated total error:      ", t.delta + r)
    print("Actual error                ", abs(expx - t.mid))
    print()
    u = t + mpi(-r, r)
    print("Interval with est. truncation error added:")
    print(u)
    print()
    print("Correct value contained in computed interval:", t.a <= expx <= t.b)
    print("When accounting for truncation error:", u.a <= expx <= u.b)

if __name__ == "__main__":
    print("Interval arithmetic demo")
    print()
    print("This script sums the Taylor series for exp(x) using interval arithmetic,")
    print("and then compares the numerical errors due to rounding and truncation.")
    print()
    x = mpf(raw_input("Enter the value of x (e.g. 3.5): "))
    n = int(raw_input("Enter the number of terms n (e.g. 10): "))
    print()
    exponential(x, n)
