def test_calc_table():
b = mcr.Batch(path="tests/example_test_input.csv")
table = b.create_table()
assert isinstance(table, pd.DataFrame)
# table.to_csv("expected_multi_table.csv")
expected_table = pd.read_csv(os.path.join(CURR_PATH,
"expected_multi_table.csv"),
index_col=0)
for col in table.columns:
assert np.allclose(table[col], expected_table[col])
def test_qbid_params():
"""
Adpots a test from Tax-Calculator that checks QBID calculations against
results from a TPC paper.
"""
tpc_path = os.path.join(CURRENT_PATH, "tpc_qbid_input.csv")
b = mcr.Batch(tpc_path)
table = b.create_table()
# QBID from TPC paper
expect_qbid = [15000, 1612.5, 0, 15000, 10750, 10000]
assert np.allclose(table["Qualified Business Income Deduction"],
expect_qbid)
def test_a18_validation():
taxcrunch_in = os.path.join(CURRENT_PATH,
"taxsim_validation/taxcrunch_in_a18.csv")
crunch = mcr.Batch(taxcrunch_in)
table_a18 = crunch.create_table()
taxsim_out = os.path.join(CURRENT_PATH,
"taxsim_validation/taxsim_out_a18.csv")
taxsim_df = pd.read_csv(taxsim_out)
taxcrunch_frate = table_a18["Income Tax MTR"] * 100
assert np.allclose(table_a18["Individual Income Tax"],
taxsim_df["fiitax"],
atol=0.01)
assert np.allclose(table_a18["Payroll Tax"], taxsim_df["fica"], atol=0.01)
assert np.allclose(taxcrunch_frate, taxsim_df["frate"], atol=0.01)
def test_get_pol_link():
b = mcr.Batch(path="tests/example_test_input.csv")
reform_preset = "Trump2016.json"
m = b.get_pol(reform_file=reform_preset)
assert m._II_rt1[2017 - 2013] == 0.12
def test_get_pol_dict():
b = mcr.Batch(path="tests/example_test_input.csv")
m = b.get_pol(reform_file=reform_dict)
assert m._CTC_c[2018 - 2013] == 1800
def test_get_pol_directory_file():
b = mcr.Batch(path="tests/example_test_input.csv")
# use the full file pathname for testing purposes
local_reform = "tests/test_reform.json"
n = b.get_pol(reform_file=local_reform)
assert n._CTC_c[2018 - 2013] == 1000
def test_get_pol_no_reform():
b = mcr.Batch(path="tests/example_test_input.csv")
assert isinstance(b, mcr.Batch)
m = b.get_pol(reform_file=None)
assert isinstance(m, tc.Policy)
import pytest
import json
import os
import numpy as np
import pandas as pd
import taxcalc as tc
import taxcrunch.cruncher as cr
import taxcrunch.multi_cruncher as mcr
CURRENT_PATH = os.path.abspath(os.path.dirname(__file__))
input_path = os.path.join(CURRENT_PATH, "example_test_input.csv")
reform_path = os.path.join(CURRENT_PATH, "test_reform.json")
b = mcr.Batch(input_path)
reform_dict = {"CTC_c": {2013: 1300, 2018: 1800}}
def test_read_input(crunch=b):
invar, invar_marg, rows = b.read_input()
assert isinstance(invar, pd.DataFrame)
assert isinstance(rows, int)
# check that number of input rows matches output rows
assert rows == len(b.create_table().index)
def test_get_pol_directory_file(crunch=b):
n = b.get_pol(reform_file=reform_path)