sensitivity_own.py

# a=[]
revenue_min_max = []
# b=[]
revenue_likely = []
# x = []
cost_min_max = []
# y=[]
cost_likely = []
# output array.
result = []

# The the amount of data we are expecting.
revenue_nos=int(input("enter revenue no. of fields"))
cost_nos=int(input("enter cost no. of fields"))

# range of revenue is of the form (min_revenue, max_revenue) and revenue_min_max
# is a list of (min, max)
print("ENTER Min and Max VALUES FOR REVENUE")
for i in range(0, revenue_nos):
    revenue_min_max.append((int(input()), int(input())))

# range of cost is of the form (min_cost, max_cost) and cost_min_max is a list
# of (min, max)
print("ENTER Min and Max VALUES FOR COST")
for i in range(0, cost_nos):
    cost_min_max.append((int(input()), int(input())))

# revenue like is a list of likely revenue values.
print("ENTER Most Likely VALUES FOR REVENUE")
for i in range(0, revenue_nos):
    revenue_likely.append(int(input()))

# cost_likely is a list of likely cost values.
print("ENTER Most Likely VALUES FOR COST")
for i in range(0, cost_nos):
    cost_likely.append(int(input()))

# sum of cost_likely array.
cost_likely_sum = sum(cost_likely)
# sum of revenue_likely array.
revenue_likely_sum = sum(revenue_likely)


for a, b in zip(revenue_min_max, revenue_likely):
    # a is (min, max), b is likely
    output = (a[0] - b + revenue_likely_sum - cost_likely_sum,
              a[1] - b + revenue_likely_sum - cost_likely_sum)
    result.append(output)

for a, b in zip(cost_min_max, cost_likely):
    # a is (min, max), b is likely.
    output = (revenue_likely_sum - (a[0] - b + cost_likely),
              revenue_likely_sum - (a[1] - b + cost_likely))
    result.append(output)


# Print output.
for each in result:
    print(each)