From 75af15ae4ac581bd16a412af256b30db3449caed Mon Sep 17 00:00:00 2001
From: Alex Moreo <alejandro.moreo@isti.cnr.it>
Date: Wed, 28 Feb 2024 08:46:54 +0100
Subject: [PATCH] force all samples be with replacement in
base.LabelledCollection, irrespective of the sample size requested
---
quapy/data/base.py | 16 ++++++----------
1 file changed, 6 insertions(+), 10 deletions(-)
diff --git a/quapy/data/base.py b/quapy/data/base.py
index 9cc6441..2629084 100644
--- a/quapy/data/base.py
+++ b/quapy/data/base.py
@@ -108,8 +108,7 @@ class LabelledCollection:
"""
Returns an index to be used to extract a random sample of desired size and desired prevalence values. If the
prevalence values are not specified, then returns the index of a uniform sampling.
- For each class, the sampling is drawn with replacement if the requested prevalence is larger than
- the actual prevalence of the class, or without replacement otherwise.
+ For each class, the sampling is drawn with replacement.
:param size: integer, the requested size
:param prevs: the prevalence for each class; the prevalence value for the last class can be lead empty since
@@ -153,7 +152,7 @@ class LabelledCollection:
for class_, n_requested in n_requests.items():
n_candidates = len(self.index[class_])
index_sample = self.index[class_][
- np.random.choice(n_candidates, size=n_requested, replace=(n_requested > n_candidates))
+ np.random.choice(n_candidates, size=n_requested, replace=True)
] if n_requested > 0 else []
indexes_sample.append(index_sample)
@@ -168,8 +167,7 @@ class LabelledCollection:
def uniform_sampling_index(self, size, random_state=None):
"""
Returns an index to be used to extract a uniform sample of desired size. The sampling is drawn
- with replacement if the requested size is greater than the number of instances, or without replacement
- otherwise.
+ with replacement.
:param size: integer, the size of the uniform sample
:param random_state: if specified, guarantees reproducibility of the split.
@@ -179,13 +177,12 @@ class LabelledCollection:
ng = RandomState(seed=random_state)
else:
ng = np.random
- return ng.choice(len(self), size, replace=size > len(self))
+ return ng.choice(len(self), size, replace=True)
def sampling(self, size, *prevs, shuffle=True, random_state=None):
"""
Return a random sample (an instance of :class:`LabelledCollection`) of desired size and desired prevalence
- values. For each class, the sampling is drawn without replacement if the requested prevalence is larger than
- the actual prevalence of the class, or with replacement otherwise.
+ values. For each class, the sampling is drawn with replacement.
:param size: integer, the requested size
:param prevs: the prevalence for each class; the prevalence value for the last class can be lead empty since
@@ -202,8 +199,7 @@ class LabelledCollection:
def uniform_sampling(self, size, random_state=None):
"""
Returns a uniform sample (an instance of :class:`LabelledCollection`) of desired size. The sampling is drawn
- with replacement if the requested size is greater than the number of instances, or without replacement
- otherwise.
+ with replacement.
:param size: integer, the requested size
:param random_state: if specified, guarantees reproducibility of the split.