Rename ConfidenceInterval to Interval

docs/general.rst

@@ -19,8 +19,8 @@ In determining whether there is *nan* in the data, only the columns specified in
 General result classes
 ----------------------
 
-.. autoclass:: yli.utils.ConfidenceInterval
-	:members:
-
 .. autoclass:: yli.utils.Estimate
 	:members:
+
+.. autoclass:: yli.utils.Interval
+	:members:

yli/distributions.py

@@ -18,7 +18,7 @@ import numpy as np
 from scipy import integrate, optimize, stats
 
 from .config import config
-from .utils import ConfidenceInterval
+from .utils import Interval
 
 class betarat_gen(stats.rv_continuous):
 	"""
@@ -343,7 +343,7 @@ def hdi(distribution, level=None):
 	:param level: Coverage/confidence probability, default (*None*) is 1 − *config.alpha*
 	:type level: float
 	
-	:rtype: :class:`yli.utils.ConfidenceInterval`
+	:rtype: :class:`yli.utils.Interval`
 	"""
 	
 	if level is None:
@@ -363,4 +363,4 @@ def hdi(distribution, level=None):
 	width = optimize_result.fun
 	upper_limit = lower_limit + width
 	
-	return ConfidenceInterval(lower_limit, upper_limit)
+	return Interval(lower_limit, upper_limit)

yli/sig_tests.py

@@ -23,7 +23,7 @@ import functools
 import warnings
 
 from .config import config
-from .utils import ConfidenceInterval, Estimate, PValueStyle, as_2groups, check_nan, convert_pandas_nullable, fmt_p
+from .utils import Estimate, Interval, PValueStyle, as_2groups, check_nan, convert_pandas_nullable, fmt_p
 
 # ----------------
 # Student's t test
@@ -268,13 +268,13 @@ class MannWhitneyResult:
 		self.med1 = med1
 		#: Median of the second group (*float*)
 		self.med2 = med2
-		#: Interquartile range of the first group (:class:`yli.utils.ConfidenceInterval`)
+		#: Interquartile range of the first group (:class:`yli.utils.Interval`)
 		self.iqr1 = iqr1
-		#: Interquartile range of the second group (:class:`yli.utils.ConfidenceInterval`)
+		#: Interquartile range of the second group (:class:`yli.utils.Interval`)
 		self.iqr2 = iqr2
-		#: Range of the first group (:class:`yli.utils.ConfidenceInterval`)
+		#: Range of the first group (:class:`yli.utils.Interval`)
 		self.range1 = range2
-		#: Range of the second group (:class:`yli.utils.ConfidenceInterval`)
+		#: Range of the second group (:class:`yli.utils.Interval`)
 		self.range2 = range2
 		
 		#: Absolute value of the rank-biserial correlation (*float*)
@@ -438,7 +438,7 @@ def mannwhitney(df, dep, ind, *, nan_policy='warn', brunnermunzel=True, use_cont
 	return MannWhitneyResult(
 		statistic=min(u1, u2), pvalue=result.pvalue,
 		group1=group1, group2=group2,
-		med1=data1.median(), med2=data2.median(), iqr1=ConfidenceInterval(data1.quantile(0.25), data1.quantile(0.75)), iqr2=ConfidenceInterval(data2.quantile(0.25), data2.quantile(0.75)), range1=ConfidenceInterval(data1.min(), data1.max()), range2=ConfidenceInterval(data2.min(), data2.max()),
+		med1=data1.median(), med2=data2.median(), iqr1=Interval(data1.quantile(0.25), data1.quantile(0.75)), iqr2=Interval(data2.quantile(0.25), data2.quantile(0.75)), range1=Interval(data1.min(), data1.max()), range2=Interval(data2.min(), data2.max()),
 		rank_biserial=r, direction=('{1} > {0}' if u1 < u2 else '{0} > {1}').format(group1, group2))
 
 # ------------------------

yli/utils.py

@@ -228,13 +228,13 @@ def fmt_p(p, style):
 # ------------------------------
 # General result-related classes
 
-class ConfidenceInterval:
-	"""A confidence interval"""
+class Interval:
+	"""An interval (e.g. confidence interval)"""
 	
 	def __init__(self, lower, upper):
-		#: Lower confidence limit (*float*)
+		#: Lower limit (*float*)
 		self.lower = lower
-		#: Upper confidence limit (*float*)
+		#: Upper limit (*float*)
 		self.upper = upper
 	
 	def __repr__(self):
@@ -247,7 +247,7 @@ class ConfidenceInterval:
 	
 	def summary(self):
 		"""
-		Return a stringified summary of the confidence interval
+		Return a stringified summary of the interval
 		
 		:rtype: str
 		"""