Increase several test tolerances to ensure tests pass on more computers

tests/test_imputed_variables.py

@@ -42,7 +42,7 @@ def actual_results(rdf, bdf):
         "OTM": {  # new OBBBA overtime income deduction
             "reform_dict": {"OvertimeIncomeDed_c": {simyear: [0, 0, 0, 0, 0]}},
             "exp_totben": 23.95,
-            "exp_affpct": 8.9,
+            "exp_affpct": 8.90,
             "exp_affben": 1401,
             # The OTM imputation calibration parameters used in the
             # create_taxcalc_imputed_variables.py module were
@@ -89,9 +89,9 @@ def actual_results(rdf, bdf):
             "exp_totben": 54.86,
             "exp_affpct": 28.06,
             "exp_affben": 1018,
-            # The affpct statistic of 28.04% and the affben statistic
-            # of $1020 are reasonably close to the Tax Policy Center
-            # estimates of 29.6% and $1081, respectively, as reported at
+            # The affpct statistic and the affben statistic are
+            # reasonably close to the Tax Policy Center estimates
+            # of 29.6% and $1081, respectively, as reported at
             # https://taxpolicycenter.org/model-estimates/T25-0257
             # Note that the $1081 TPC estimate is derived by dividing
             # the all-unit average of $320 by the 0.296 affpct.
@@ -115,6 +115,11 @@ def actual_results(rdf, bdf):
     bdf = baseline_sim.dataframe(output_variables)
     # estimate effects of each new OBBBA deduction
     diffs = []  # list of act-vs-exp differences
+    abs_tolerance = {
+        "totben": 0.01,  # to handle round(x, 2) logic
+        "affpct": 0.01,  # to handle round(x, 2) logic
+        "affben": 1.00,  # to handle round(x, 0) logic
+    }
     for ded, info in deductions.items():
         # create reform Calculator object for simyear
         reform_policy = tc.Policy()
@@ -130,8 +135,9 @@ def actual_results(rdf, bdf):
         for stat in ["totben", "affpct", "affben"]:
             act = act_res[stat]
             exp = info[f"exp_{stat}"]
-            if not np.allclose([act], [exp]):
-                diff = f"DIFF:{ded},{stat},act,exp= {act} {exp}"
+            a_tol = abs_tolerance[stat]
+            if not np.allclose([act], [exp], atol=a_tol):
+                diff = f"DIFF:{ded},{stat},act,exp,atol= {act} {exp} {a_tol}"
                 diffs.append(diff)
         # delete reform Policy and Calculator objects
         del reform_policy

tests/test_tax_expenditures.py

@@ -3,10 +3,8 @@
 against expected tax expenditure values in the tests folder.
 """
 
-import difflib
 import pytest
 import numpy as np
-import pandas as pd
 from tmd.storage import STORAGE_FOLDER
 from tmd.create_taxcalc_input_variables import TAXYEAR
 from tmd.utils.taxcalc_utils import get_tax_expenditure_results
@@ -27,26 +25,28 @@ def test_tax_exp_diffs(
         tmd_growfactors_path,
     )
     act_path = STORAGE_FOLDER / "output" / "tax_expenditures"
-    exp_path = tests_folder / "expected_tax_expenditures"
-    actdf = pd.read_csv(act_path, sep=" ", header=None)
-    expdf = pd.read_csv(exp_path, sep=" ", header=None)
-    assert actdf.shape == expdf.shape, "actdf and expdf are not the same shape"
-    # compare actdf and expdf rows
-    same = True
-    actval = actdf.iloc[:, 3].to_numpy(dtype=np.float64)
-    expval = expdf.iloc[:, 3].to_numpy(dtype=np.float64)
-    if not np.allclose(actval, expval):
-        same = False
-    if same:
-        return
-    # if same is False
     with open(act_path, "r", encoding="utf-8") as actfile:
         act = actfile.readlines()
+    exp_path = tests_folder / "expected_tax_expenditures"
     with open(exp_path, "r", encoding="utf-8") as expfile:
         exp = expfile.readlines()
-    diffs = list(
-        difflib.context_diff(act, exp, fromfile="actual", tofile="expect", n=0)
-    )
+    assert len(act) == len(exp), "number of act and exp rows differ"
+    a_tol = 0.1  # handles :.1f rounding of tax expenditures
+    r_tol = 5e-5  # larger than the np.allclose default value of 1e-5
+    diffs = []
+    for rowidx, act_row in enumerate(act):
+        atok = act_row.split()
+        etok = exp[rowidx].split()
+        for tokidx in range(3):
+            assert atok[tokidx] == etok[tokidx], "act vs exp tokens differ"
+        act_val = float(atok[3])
+        exp_val = float(etok[3])
+        if not np.allclose([act_val], [exp_val], atol=a_tol, rtol=r_tol):
+            msg = (
+                f"{atok[2]},act,exp,atol,rtol= "
+                f"{act_val} {exp_val} {a_tol} {r_tol}\n"
+            )
+            diffs.append(msg)
     if len(diffs) > 0:
         emsg = "\nACT-vs-EXP TAX EXPENDITURE DIFFERENCES:\n" + "".join(diffs)
         raise ValueError(emsg)

tests/test_weights.py

@@ -14,12 +14,13 @@ def test_weights(tmd_variables):
     wght = tmd_variables["s006"].to_numpy()
     actual = {"mean": wght.mean(), "sdev": wght.std()}
     expect = {"mean": 815.5521277934885, "sdev": 961.7270821801824}
+    r_tol = 7e-5  # larger than the np.allclose default value of 1e-5
     diffs = []
     for stat in ["mean", "sdev"]:
         act = actual[stat]
         exp = expect[stat]
-        if not np.allclose([act], [exp]):
-            diff = f"WEIGHT_DIFF:{stat},act,exp= {act} {exp}"
+        if not np.allclose([act], [exp], rtol=r_tol):
+            diff = f"WEIGHT_DIFF:{stat},act,exp,rtol= {act} {exp} {r_tol}"
             diffs.append(diff)
     if diffs:
         emsg = "\nWEIGHT VARIABLE ACT-vs-EXP DIFFS:"