How convert user inputted constant (pi,e) to float in python?
Question:
I’m writing a code which must compute definite integral of a function. I’ll provide code in the below. How can I urge computer to understand user input “pi” or “e” for constant numbers? Problem is that I must convert the type of input to float, for following calculations. So when user inputs pi it’s raising ValueError. How can we get constants like pi to give bounds?
from sympy import *
from sympy.abc import *
import math
import numpy as np
import time
import sys
import pandas as pd
############ ############
####### Calculating Definite Integral of a given function using trapezium method #######
######### ##############
cuts = 100 #is number of cuts
########################## DataFrame object of aveliable differantiable functions
all_functions = {"Trigonometric": ["sin", "cos",'tan','cot','sec','csec','sinc'],
"Trigonometric Inverses": ["asin", "acos",'atan','acot','asec','acsec'," "],
'Hyperbolic Functions': [ 'sinh', 'cosh', 'tanh', 'coth'," "," "," "],
'Hyperbolic Inverses':['asinh','acosh','atanh','acoth','asech','acsch'," "],
"Exponential": ["exp", 'log','ln',"log(base,x)", ' ', " "," "],
"Roots":["root","sqrt",'cbrt',' '," "," "," "],
"Powers": ["x**n (n is all real numbers)"," "," "," "," "," "," "],
"Combinatorical": ['factorial'," "," "," "," "," "," "]}
df = pd.DataFrame(all_functions,index = [" "," "," "," "," "," "," "])
df.columns.name = "Funcion'c classes"
df.index.name = "Functions"
df = df.T
###############################################
#####Defining functions which will compute integral using trapezium method
##### Trapezium method fomrula -- Integral(f(x),a,b) = (a-b)/n * ( (y_0+y_n)/2 + y_1+y_2+...+ y_(n-1) )
def integral():
print("Enter Function to integrate: ", end=" ")
function = sympify(input()) #converting string input to sympy expression
print("Enter lower bound: ", end = " ")
lower = float(input()) #lower bound of definite integral
print("Enter upper bound: ", end = " ")
upper = float(input()) # upper bound of definite integral
xi = np.linspace(lower,upper,cuts+1) #cutting X axis to n+1 parts, for x0=a<x1<x2<...xi<x(i+1)<...<xn=b
####### y_i = function(x_i) ########inserting "x"s in function and computing y values, for using trapezium method formula
ylist = []
for i in range(len(xi)):
ys = function.subs(x,xi[i])
ylist.append(ys)
sum2 = 0 #second part of trapezium method sum
for j in range(1,cuts):
sum2 = sum2 + ylist[j]
sum1 = (ylist[0]+ylist[cuts])/2 #first part of trapezium method sum
result = (upper-lower)*(sum1+sum2)/cuts #result of an integral
####computing error of an integral
derivative = diff(function,x,2) #2nd differential of function at given point
derresult = derivative.subs(x,(lower-upper)/2) #result of derivative of
error = abs((upper-lower)**3*derresult/(12*cuts**12)) #error of definite integral
dots = "Integrating....n"
####typing ^^^ this line alternatly
for l in dots:
sys.stdout.write(l)
sys.stdout.flush()
time.sleep(0.045)
equals = "================nn"
####typing ^^^ this line alternatly
for l in equals:
sys.stdout.write(l)
sys.stdout.flush()
time.sleep(0.045)
#raise this error when bounds give infinity result
if result == math.inf or result == -math.inf:
print("Bounds are false")
else:
###printing integral result
print("Derfinite integral of " + str(function) +" from " +str(lower)+" to "+ str(upper)+" = "+ "%.5f +- %e" %(result, error)+"n")
######## typing equlas alternatly
for l in equals:
sys.stdout.write(l)
sys.stdout.flush()
time.sleep(0.055)
try: ### Trye integral() function if errors are occuring execute excepts
integral()
except TypeError: ##execute this when TypeError occured , i.e. function typed incorrectly
print("The Function You have entered does not exist or is not differentiable or consists other symbol ranther then 'x' !nTo see list of all differentiable functions please type "Functions" n")
function_input = input()
function_list = ["Functions", "Function","functions",'function',"FUNCTIONS",'FUNCTIONS']
if function_input in function_list: #if user input is correct print out DataFrame of aveliable functions, and excecute integral()
print(df, end = "nn")
integral()
else: #if user input is incorrect return statement below, which will wait to user input print out function's list and excecute integral()
print("Please Type 'Functions' correctly")
function_input = input()
print(df, end = "nn")
integral()
except SympifyError:
print("nExpression You have entered is not a fully written function or not not written correctly.n")
integral()
except ValueError:
print("nBounds must be numbers.n")
integral()
Answers:
You can write a function that recognizes certain names before calling float() to parse it normally.
def my_float(s):
constants = {"pi": 3.14159, "e": 2.71928}
if s in constants:
return constants[s]
else:
return float(s)
Then you can read write:
print("Enter lower bound: ", end = " ")
lower = my_float(input()) #lower bound of definite integral
you can use this code:
from numpy import pi,e
value = eval(input()) # if you entered "pi", value will be = 3.14
print(value)`
I’m writing a code which must compute definite integral of a function. I’ll provide code in the below. How can I urge computer to understand user input “pi” or “e” for constant numbers? Problem is that I must convert the type of input to float, for following calculations. So when user inputs pi it’s raising ValueError. How can we get constants like pi to give bounds?
from sympy import *
from sympy.abc import *
import math
import numpy as np
import time
import sys
import pandas as pd
############ ############
####### Calculating Definite Integral of a given function using trapezium method #######
######### ##############
cuts = 100 #is number of cuts
########################## DataFrame object of aveliable differantiable functions
all_functions = {"Trigonometric": ["sin", "cos",'tan','cot','sec','csec','sinc'],
"Trigonometric Inverses": ["asin", "acos",'atan','acot','asec','acsec'," "],
'Hyperbolic Functions': [ 'sinh', 'cosh', 'tanh', 'coth'," "," "," "],
'Hyperbolic Inverses':['asinh','acosh','atanh','acoth','asech','acsch'," "],
"Exponential": ["exp", 'log','ln',"log(base,x)", ' ', " "," "],
"Roots":["root","sqrt",'cbrt',' '," "," "," "],
"Powers": ["x**n (n is all real numbers)"," "," "," "," "," "," "],
"Combinatorical": ['factorial'," "," "," "," "," "," "]}
df = pd.DataFrame(all_functions,index = [" "," "," "," "," "," "," "])
df.columns.name = "Funcion'c classes"
df.index.name = "Functions"
df = df.T
###############################################
#####Defining functions which will compute integral using trapezium method
##### Trapezium method fomrula -- Integral(f(x),a,b) = (a-b)/n * ( (y_0+y_n)/2 + y_1+y_2+...+ y_(n-1) )
def integral():
print("Enter Function to integrate: ", end=" ")
function = sympify(input()) #converting string input to sympy expression
print("Enter lower bound: ", end = " ")
lower = float(input()) #lower bound of definite integral
print("Enter upper bound: ", end = " ")
upper = float(input()) # upper bound of definite integral
xi = np.linspace(lower,upper,cuts+1) #cutting X axis to n+1 parts, for x0=a<x1<x2<...xi<x(i+1)<...<xn=b
####### y_i = function(x_i) ########inserting "x"s in function and computing y values, for using trapezium method formula
ylist = []
for i in range(len(xi)):
ys = function.subs(x,xi[i])
ylist.append(ys)
sum2 = 0 #second part of trapezium method sum
for j in range(1,cuts):
sum2 = sum2 + ylist[j]
sum1 = (ylist[0]+ylist[cuts])/2 #first part of trapezium method sum
result = (upper-lower)*(sum1+sum2)/cuts #result of an integral
####computing error of an integral
derivative = diff(function,x,2) #2nd differential of function at given point
derresult = derivative.subs(x,(lower-upper)/2) #result of derivative of
error = abs((upper-lower)**3*derresult/(12*cuts**12)) #error of definite integral
dots = "Integrating....n"
####typing ^^^ this line alternatly
for l in dots:
sys.stdout.write(l)
sys.stdout.flush()
time.sleep(0.045)
equals = "================nn"
####typing ^^^ this line alternatly
for l in equals:
sys.stdout.write(l)
sys.stdout.flush()
time.sleep(0.045)
#raise this error when bounds give infinity result
if result == math.inf or result == -math.inf:
print("Bounds are false")
else:
###printing integral result
print("Derfinite integral of " + str(function) +" from " +str(lower)+" to "+ str(upper)+" = "+ "%.5f +- %e" %(result, error)+"n")
######## typing equlas alternatly
for l in equals:
sys.stdout.write(l)
sys.stdout.flush()
time.sleep(0.055)
try: ### Trye integral() function if errors are occuring execute excepts
integral()
except TypeError: ##execute this when TypeError occured , i.e. function typed incorrectly
print("The Function You have entered does not exist or is not differentiable or consists other symbol ranther then 'x' !nTo see list of all differentiable functions please type "Functions" n")
function_input = input()
function_list = ["Functions", "Function","functions",'function',"FUNCTIONS",'FUNCTIONS']
if function_input in function_list: #if user input is correct print out DataFrame of aveliable functions, and excecute integral()
print(df, end = "nn")
integral()
else: #if user input is incorrect return statement below, which will wait to user input print out function's list and excecute integral()
print("Please Type 'Functions' correctly")
function_input = input()
print(df, end = "nn")
integral()
except SympifyError:
print("nExpression You have entered is not a fully written function or not not written correctly.n")
integral()
except ValueError:
print("nBounds must be numbers.n")
integral()
You can write a function that recognizes certain names before calling float() to parse it normally.
def my_float(s):
constants = {"pi": 3.14159, "e": 2.71928}
if s in constants:
return constants[s]
else:
return float(s)
Then you can read write:
print("Enter lower bound: ", end = " ")
lower = my_float(input()) #lower bound of definite integral
you can use this code:
from numpy import pi,e
value = eval(input()) # if you entered "pi", value will be = 3.14
print(value)`