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TPTBusiness
ba4d64b434
The fixer was raising min_periods to match window size, which causes all-NaN output for intraday factors with 96 bars/day — window=240 means zero valid bars per day, window=60 means 61% NaN per day. Critics were consistently flagging this as incorrect for intraday factors. The LLM now controls its own min_periods. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
98 lines
3.9 KiB
Python
98 lines
3.9 KiB
Python
"""Tests for FactorAutoFixer — the pre-execution code patcher."""
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import pytest
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from rdagent.components.coder.factor_coder.auto_fixer import FactorAutoFixer
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@pytest.fixture()
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def fixer():
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return FactorAutoFixer()
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class TestResetIndexGroupby:
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def test_replaces_level_groupby_on_reset_var(self, fixer):
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code = "df_r = df.reset_index()\ndf_r['x'] = df_r.groupby(level=1)['$close'].mean()"
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result = fixer.fix(code)
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assert "groupby('instrument')" in result
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def test_does_not_touch_normal_multiindex_groupby(self, fixer):
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code = "df['x'] = df.groupby(level=1)['$close'].mean()"
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result = fixer.fix(code)
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assert "groupby(level=1)" in result
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class TestGroupbyMixedLevels:
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def test_strips_string_from_mixed_list(self, fixer):
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result = fixer.fix("df.groupby(level=[1, 'date']).apply(fn)")
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assert "groupby(level=1)" in result
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def test_multiple_ints_kept(self, fixer):
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result = fixer.fix("df.groupby(level=[0, 1, 'x']).apply(fn)")
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assert "groupby(level=[0, 1])" in result
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class TestGroupbyColumnOnMultiindex:
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def test_instrument_date_becomes_two_level(self, fixer):
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code = "df['v'] = df.groupby(['instrument', 'date'])['$volume'].cumsum()"
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result = fixer.fix(code)
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assert "get_level_values(1)" in result
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assert "normalize()" in result
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assert "level=1)" not in result.split("get_level_values")[0]
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def test_date_instrument_becomes_two_level(self, fixer):
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code = "df['v'] = df.groupby(['date', 'instrument'])['$volume'].cumsum()"
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result = fixer.fix(code)
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assert "get_level_values(0).normalize()" in result
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assert "get_level_values(1)" in result
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def test_single_instrument_becomes_level1(self, fixer):
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result = fixer.fix("df.groupby(['instrument'])['x'].mean()")
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assert "groupby(level=1)" in result
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def test_reset_index_not_double_fixed(self, fixer):
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# After reset_index fix emits groupby('instrument'), this fixer must NOT
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# convert that to groupby(level=1).
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code = "df_r = df.reset_index()\ndf_r['x'] = df_r.groupby(level=1)['p'].mean()"
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result = fixer.fix(code)
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assert "groupby('instrument')" in result
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class TestChainedGroupby:
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def test_chained_groupby_level_then_date(self, fixer):
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code = "df.groupby(level=1).groupby('date')['price_volume'].transform('cumsum')"
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result = fixer.fix(code)
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assert "get_level_values(1)" in result
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assert "get_level_values(0).normalize()" in result
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assert ".groupby('date')" not in result
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def test_chained_groupby_with_double_quotes(self, fixer):
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code = 'df.groupby(level=0).groupby("date")["col"].sum()'
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result = fixer.fix(code)
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assert "get_level_values" in result
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assert '.groupby("date")' not in result
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class TestMinPeriodsNotTouched:
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def test_small_min_periods_preserved(self, fixer):
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# _fix_min_periods is disabled — LLM-set min_periods must not be changed.
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# window=60, min_periods=1 should stay as-is (was wrongly raised to 60 before).
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result = fixer.fix("df.groupby(level=1)['x'].transform(lambda x: x.rolling(window=60, min_periods=1).mean())")
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assert "min_periods=1" in result
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def test_large_window_min_periods_preserved(self, fixer):
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# window=240 > 96 bars/day: if min_periods were set to 240 the output would be
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# all-NaN for intraday data. Verify we leave it untouched.
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result = fixer.fix("df['x'] = df.groupby(level=1)['y'].transform(lambda x: x.rolling(240, min_periods=10).std())")
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assert "min_periods=10" in result
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class TestRollingDdof:
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def test_removes_ddof_from_rolling_args(self, fixer):
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result = fixer.fix("df.rolling(20, min_periods=1, ddof=1).std()")
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assert "ddof" not in result
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def test_removes_ddof_from_std_args(self, fixer):
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result = fixer.fix("df.rolling(20).std(ddof=1)")
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assert "ddof" not in result
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