quartile

module00/ex01/TinyStatistician.py

@@ -38,7 +38,7 @@ def median(x: np.ndarray) -> float | None:
 
 	@staticmethod
 	@accepts(np.ndarray)
-	def quartiles(x: np.ndarray) -> list[float] | None:
+	def quartile(x: np.ndarray) -> list[float] | None:
 		arr = np.sort(x)
 		middle_index = arr.shape[0] // 2
 		if arr.shape[0] % 2 == 1:
@@ -51,12 +51,11 @@ def quartiles(x: np.ndarray) -> list[float] | None:
 	@accepts(np.ndarray, (int, float))
 	def percentile(x: np.ndarray, p: float | int) -> float | None:
 		arr = np.sort(x)
-		idx = (arr.shape[0] - 1) * p / 100
+		idx = (arr.shape[0] - 1) * (p / 100)
 		if idx.is_integer():
 			return arr[idx]
-		f, c = int(idx), int(idx + 1.0)
-		f_diff, c_diff = idx - f, c - idx
-		return c_diff * arr[f] + f_diff * arr[c]
+		floor, ceiling = int(idx), int(idx + 1.0)
+		return arr[floor] + (idx - floor) * (arr[ceiling] - arr[floor])
 
 	@staticmethod
 	@accepts(np.ndarray)
@@ -68,37 +67,3 @@ def var(x: np.ndarray) -> float | None:
 	@accepts(np.ndarray)
 	def std(x: np.ndarray) -> float | None:
 		return sqrt(TinyStatistician.var(x))
-
-
-def main() -> None:
-	tstat = TinyStatistician()
-	a = np.array([1, 42, 300, 10, 59])
-	mean = tstat.mean(a)
-	print(f'{mean = }')
-	assert mean == 82.4
-	median = tstat.median(a)
-	print(f'{median = }')
-	assert median == 42.0
-	quartiles = tstat.quartiles(a)
-	print(f'{quartiles = }')
-	assert quartiles == [10.0, 59.0]
-	variance = tstat.var(a)
-	print(f'{variance = }')
-	assert variance == 15349.3
-	std_deviation = tstat.std(a)
-	print(f'{std_deviation = }')
-	assert std_deviation == 123.89229193133849
-
-	percentiles: dict = {
-		10: tstat.percentile(a, 10),
-		15: tstat.percentile(a, 15),
-		20: tstat.percentile(a, 20)
-	}
-	print(f'{percentiles = }')
-	assert percentiles[10] == 4.6, f'I came up with {percentiles[10]}'
-	assert percentiles[15] == 6.4, f'I came up with {percentiles[15]}'
-	assert percentiles[20] == 8.2, f'I came up with {percentiles[20]}'
-
-
-if __name__ == '__main__':
-	main()

module00/ex01/test.py

@@ -0,0 +1,36 @@
+from TinyStatistician import TinyStatistician
+import numpy as np
+
+
+def main() -> None:
+	tstat = TinyStatistician()
+	a = np.array([1, 42, 300, 10, 59])
+	mean = tstat.mean(a)
+	print(f'{mean = }')
+	assert mean == 82.4
+	median = tstat.median(a)
+	print(f'{median = }')
+	assert median == 42.0
+	quartiles = tstat.quartile(a)
+	print(f'{quartiles = }')
+	assert quartiles == [10.0, 59.0]
+	variance = tstat.var(a)
+	print(f'{variance = }')
+	assert variance == 15349.3
+	std_deviation = tstat.std(a)
+	print(f'{std_deviation = }')
+	assert std_deviation == 123.89229193133849
+
+	percentiles: dict = {
+		10: tstat.percentile(a, 10),
+		15: tstat.percentile(a, 15),
+		20: tstat.percentile(a, 20)
+	}
+	print(f'{percentiles = }')
+	assert abs(percentiles[10] - 4.6) < 1e-5, f'I came up with {percentiles[10]}'
+	assert abs(percentiles[15] - 6.4) < 1e-5, f'I came up with {percentiles[15]}'
+	assert abs(percentiles[20] - 8.2) < 1e-5, f'I came up with {percentiles[20]}'
+
+
+if __name__ == '__main__':
+	main()