def test_calc_add_life():
calc = Calc()
result = calc.add_life(age=30, qx=get_qx())
assert result == "x1"
assert "x1" in calc.columns
assert "q(x1)" in calc.columns
assert calc["x1"].iloc[0] == 30
import pytest
from actymath import Calc
from actymath.tables import A1967_70_Exams
# A1967-70 table - Actuarial Green tables for testing
table = A1967_70_Exams()
q0 = table.qx(0, select=True)
# Create calc
calc = Calc()
calc.add_life(0, q0)
calc.add_i(rate=0.04) # Will use 4% tables
# Set the l(x) with the right base for the tables
calc.populate("l(x1)")
def test_a_due_x1():
calc.populate("a_due(x1)")
assert calc["a_due(x1)"].iloc[0] == pytest.approx(24.240, abs=0.001)
assert calc["a_due(x1)"].iloc[54] == pytest.approx(14.672, abs=0.001)
def test_a_x1():
calc.populate("a(x1)")
assert calc["a(x1)"].iloc[53] == pytest.approx(14.672 * 3840.1664 /
4020.9326,
abs=0.001)
def test_A_x1():
import pandas as pd
import pytest
from actymath import Calc
from actymath.tables import A1967_70_Exams
# A1967-70 table - Actuarial Green tables for testing
table = A1967_70_Exams()
q45 = table.qx(45, select=True)
# Create calc
calc = Calc()
calc.add_life(45, q45)
calc.add_i(rate=0.04) # Will use 4% tables
def test_t():
calc.populate("t")
assert calc["t"].iloc[0] == 0
assert calc["t"].iloc[25] == 25
def test_n():
calc.add_term(n=10)
calc.add_term(n=20)
assert calc["n1"].iloc[0] == 10
assert calc["n1"].iloc[10] == 0
assert pd.isnull(calc["n1"].iloc[11])
assert calc["n2"].iloc[0] == 20
assert calc["n2"].iloc[10] == 10
def test_calc_is_dataframe():
calc = Calc()
assert isinstance(calc, pd.DataFrame)
import pytest
from actymath import Calc, ActyMathError
from actymath.tables import A1967_70_Exams
# A1967-70 table - Actuarial Green tables for testing
table = A1967_70_Exams()
q0 = table.qx(0, select=True)
# Create calc
calc = Calc()
calc.add_life(0, q0)
calc.add_i(rate=0.04) # Will use 4% tables
def test_qx1():
assert calc["q(x1)"].iloc[0] == pytest.approx(0.00058, abs=0.00001)
assert calc["q(x1)"].iloc[4] == pytest.approx(0.00053, abs=0.00001)
def test_px1():
calc.populate("p(x1)")
assert calc["p(x1)"].iloc[0] == pytest.approx(1 - 0.0005800)
assert calc["p(x1)"].iloc[4] == pytest.approx(1 - 0.00053000)
def test_lx1():
calc.populate("l(x1)")
assert calc["l(x1)"].iloc[0] == pytest.approx(34481.408)
assert calc["l(x1)"].iloc[4] == pytest.approx(34398.727)
assert calc["l(x1)"].iloc[54] == pytest.approx(31926.430)
import pandas as pd
import pytest
from actymath import Calc
from actymath.tables import A1967_70_Exams
# A1967-70 table - Actuarial Green tables for testing
table = A1967_70_Exams()
q45 = table.qx(45, select=True) # Select
q54 = table.qx(54, select=False) # Ultimate
# Create calc
calc = Calc()
calc.add_life(45, q45)
calc.add_i(rate=0.04) # Will use 4% tables
calc.add_term(n=10) # Will use the x+n = 55 tables in Green tables for tests
# Set the l(x) with the right base for the tables
calc.populate("l(x1)")
calc54 = Calc() # 54 year old
calc54.add_life(54, q54)
calc54.add_i(rate=0.04) # Will use 4% tables
calc54.add_term(n=10)
calc54.populate("l(x1)")
def test_a_due_x1_n1():
calc.populate("a_due(x1)[n1]")
assert calc["a_due(x1)[n1]"].iloc[0] == pytest.approx(8.317,
abs=0.001) # Select
assert calc["a_due(x1)[n1]"].iloc[5] == pytest.approx(