feat(browser): auto-commit con 178 cambios

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/functions/datascience/trend_slope_test.py

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+"""Tests para trend_slope."""
+
+import random
+
+from trend_slope import trend_slope
+
+
+def test_increasing_series_slope_positive_up_significant():
+    values = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
+    result = trend_slope(values)
+    assert result["slope"] is not None
+    assert result["slope"] > 0
+    assert result["direction"] == "up"
+    assert result["significant"] is True
+    assert result["n"] == 10
+
+
+def test_decreasing_series_slope_negative_down_significant():
+    values = [10, 9, 8, 7, 6, 5, 4, 3, 2, 1]
+    result = trend_slope(values)
+    assert result["slope"] < 0
+    assert result["direction"] == "down"
+    assert result["significant"] is True
+
+
+def test_flat_constant_series_not_significant():
+    values = [5.0] * 12
+    result = trend_slope(values)
+    assert result["direction"] == "flat"
+    assert result["significant"] is False
+
+
+def test_random_series_flat_not_significant():
+    rng = random.Random(42)
+    values = [rng.gauss(0, 1) for _ in range(60)]
+    result = trend_slope(values)
+    assert result["direction"] == "flat"
+    assert result["significant"] is False
+
+
+def test_custom_x_axis():
+    x = [0, 10, 20, 30, 40]
+    values = [1, 3, 5, 7, 9]
+    result = trend_slope(values, x)
+    assert result["slope"] > 0
+    assert result["direction"] == "up"
+    assert abs(result["r_squared"] - 1.0) < 1e-9
+
+
+def test_too_few_pairs_returns_none_slope():
+    result = trend_slope([1, 2])
+    assert result["slope"] is None
+    assert result["direction"] == "unknown"
+    assert result["significant"] is False
+    assert result["n"] == 2
+
+
+def test_drops_none_and_nan_pairs():
+    values = [1, None, 3, float("nan"), 5, 6, 7]
+    result = trend_slope(values)
+    assert result["n"] == 5
+    assert result["slope"] > 0
+    assert result["direction"] == "up"
+
+
+def test_too_few_valid_pairs_after_dropping():
+    values = [1, None, None, float("nan"), 5]
+    result = trend_slope(values)
+    assert result["slope"] is None
+    assert result["direction"] == "unknown"
+    assert result["n"] == 2