From f962322b42778deded738a72ae44cfe6ce047e9b Mon Sep 17 00:00:00 2001 From: kwinkunks Date: Mon, 4 Sep 2023 08:14:08 +0200 Subject: [PATCH] fix #53 --- src/redflag/utils.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/redflag/utils.py b/src/redflag/utils.py index cc403f9..1d5f2e7 100644 --- a/src/redflag/utils.py +++ b/src/redflag/utils.py @@ -355,7 +355,7 @@ def is_standardized(a: ArrayLike, atol: float=1e-3) -> bool: return bool((np.abs(μ) < atol) and (np.abs(σ - 1) < atol)) -def is_standard_normal(a: ArrayLike, confidence: float=0.95) -> bool: +def is_standard_normal(a: ArrayLike, confidence: float=0.8) -> bool: """ Performs the Kolmogorov-Smirnov test for normality. Returns True if the feature appears to be normally distributed, with a mean close to zero and @@ -363,15 +363,15 @@ def is_standard_normal(a: ArrayLike, confidence: float=0.95) -> bool: Args: a (array): The data. - confidence (float): The confidence level of the test, default 0.95 - (95% confidence). + confidence (float): The confidence level of the test, default 0.8 + (80% confidence). Returns: bool: True if the feature appears to have a standard normal distribution. Example: - >>> a = np.random.normal(size=2000) - >>> is_standard_normal(a, confidence=0.9) + >>> a = np.random.normal(size=2500) + >>> is_standard_normal(a, confidence=0.8) True >>> is_standard_normal(a + 1) False